{"id":2401,"date":"2015-11-22T10:19:29","date_gmt":"2015-11-22T15:19:29","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/automation-at-the-associated-press-could-a-robot-have-written-this-blog-post\/"},"modified":"2015-11-22T16:25:51","modified_gmt":"2015-11-22T21:25:51","slug":"automation-at-the-associated-press-could-a-robot-have-written-this-blog-post","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/automation-at-the-associated-press-could-a-robot-have-written-this-blog-post\/","title":{"rendered":"Automation at The Associated Press: Could a robot have written this blog post?"},"content":{"rendered":"

~~ Update: For a brilliant\u00a0and breathtaking\u00a0example of automatically generated news\u00a0based on audience input, as per the last section of this post, see Sunday’s\u00a0New York Times interactive describing all 649 nonillion ways the NFL season could end<\/a>. I mean, wow. ~~<\/em><\/p>\n

In the summer of 2014, the Associated Press did something that, to many journalists, was straight out of science fiction. It began assigning\u00a0earnings reports stories to robots<\/a>.<\/p>\n

It was able to\u00a0do this for two reasons, both related to data. The AP recognized that much of the information in companies’ quarterly reports could easily be read as\u00a0structured data — data that’s organized in\u00a0a predictable structure, and therefore easily read by a machine. Additionally, computable comparisons between data determined the angle of and details in the stories. Did a company perform better or worse than expected? Compare its current earnings to analyst predictions. Was it just shy of expectations or did it miss them entirely?\u00a0Compare the difference between expectations and performance.<\/p>\n

Get the data, add a carefully crafted\u00a0algorithm, and you’ve got an automatically generated news story.<\/p>\n

Using Wordsmith, automation software from North Carolina-based Automated Insights<\/a>, the Associated Press now creates about 3,500 stories per quarter using automation, and expects to produce 4,500 such stories by the end of 2015<\/strong>, it told Nieman Reports<\/a>. In January, the company said its automated stories had already\u00a0increased the company’s story output tenfold<\/strong>. Today, editors estimate that the stories have freed up as much as 20 percent of its business reporters’ time to work on other content<\/strong>.<\/p>\n

“Every time you\u2019re freeing up a staffer\u2019s time, or somebody\u2019s time, that time is going elsewhere to do something that is more relevant in the modern media world we\u2019re living in,” Lou Ferrara, the AP’s vice president and managing editor, told Poynter<\/a>.<\/p>\n

 <\/p>\n

\"How<\/a>
How an algorithm builds a story. Screenshot from Wired<\/a>.<\/figcaption><\/figure>\n

 <\/p>\n

A NEW VALUE CREATION STRATEGY<\/strong><\/p>\n

Founded in 1846, the Associated Press is one of the oldest and largest newsgathering operations in the world<\/a>. It’s a not-for-profit cooperative owned by its members, a host of American broadcast and news organizations, who support it with licensing fees.\u00a0In 2014<\/a>, 47 percent of the AP’s\u00a0$604 million in revenue came from broadcasters, 25 percent from newspapers, 9 percent from Internet companies, 7 percent from other agencies, and 5 percent from radio stations.<\/strong><\/p>\n

Though automated earnings stories free up plenty of the AP’s resources for value creation, the company\u00a0doesn’t see them\u00a0as a way to grow revenue from\u00a0its local markets — yet. But the stories are helping the company\u00a0reshape its strategy to better serve its local customers, whom it hopes\u00a0to retain despite job cuts and losses across the industry. Most of the AP’s customers are local news operations, and the AP has had to cut back on coverage of local companies as it’s struggled under\u00a0its own financial strain (it posted its first revenue gain in six years in 2014<\/a>).<\/p>\n

Thanks to its output of automated stories, the AP has been able to restore its coverage of more local and regional companies, and then some.\u00a0It’s programmed its automated system to gather data and produce earnings stories for all companies with a market capitalization of $75 million or greater, a number that could never have been covered by its staff reporters. With the AP supplying basic earnings reports stories, local business reporters can focus on more in-depth work.<\/p>\n

 <\/p>\n

THE BENEFIT OF SPEED<\/strong><\/p>\n

As a wire service for other news organizations, the Associated Press’ customers value few things more than speed — especially with business critical information like earnings reports. In that respect, if there were\u00a0a way to speed up the deployment of basic stories to its customers and the AP didn’t take advantage of it, it could lose competitive ground\u00a0to someone who did.<\/p>\n

It is no surprise, then, that the AP has done so much so early to develop\u00a0automation. It’s getting ahead of the industry. Before the AP\u00a0deployed its automation\u00a0technology, staffers pushed to post\u00a0130-word earnings stories on the wire within 20 minutes of a press release — no easy feat for a human staffer. The AP now gets 500-word stories on the wire within a minute of a press release — and can generate 2,000 stories a second<\/strong>, according to stats shared with Nieman Reports<\/a>.<\/p>\n

 <\/p>\n

COMING UP: STORIES BASED ON READER DATA<\/strong><\/p>\n

The AP, along with the rest of the news industry, is just beginning to deploy story automation to assist in its value creation for readers and customers. Earnings stories were just the first step for the AP. They’re experimenting with automating sports stories and even election stories with returns from local polling stations. Anywhere\u00a0structured data is news, automation can give a big assist.<\/p>\n

The next big step with news\u00a0automation will likely be fueled not by data about the story, but about the reader. The New York Times,\u00a0ProPublica<\/a> and others have already published one-off projects that customize stories to different readers based on those readers’ locations or expectations. As University of Maryland Francis King Carey School of Law professor Frank Pasquale told Nieman Reports<\/a>, if stories can be tailored for users based on things like income, geography or other characteristics, newsrooms will soon feel pressure to do it. “That’s going to be seen, eventually, as revenue maximizing,” he said. He’s right.<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

The AP is using algorithms to automatically generate news stories from structured data. 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