Nick Diakopoulos checks ’em out:
Every robot journalist first needs to ingest a bunch of data. Data rich domains like weather were some of the first to have practical natural language generation systems. Now we’re seeing a lot of robot journalism applied to sports and finance — domains where the data can be standardized and made fairly clean. The development of sensor journalism may provide entirely new troves of data for producing automated stories. …
After data is read in by the algorithm the next step is to compute interesting or newsworthy features from the data. Basically the algorithm is trying to figure out the most critical aspects of an event, like a sports game. It has newsworthiness criteria built into its statistics. So for example, it looks for surprising statistical deviations like minimums, maximums, or outliers, big swings and changes in a value, violations of an expectation, a threshold being crossed, or a substantial change in a predictive model.
Joe Pinsker isn’t too worried about robot-written stories corroding journalism:
These automated write-ups are for now filling micro-niches, such as Little League games or fantasy football drafts, that are outside the scope of information covered by journalists working now.
As Automated Insights’ CEO Robbie Allen told Poynter, “We’re creating content where it didn’t exist before.” The AP’s move has a similar underlying goal: It said that Automated Insights’ algorithms will allow them to produce nearly 15 times as many earnings reports per quarter than when they filed them manually.
While, yes, it’s true that algorithms can cram stories about vastly different subjects into the same uncanny monotone—they can cover Little League like Major League Baseball, and World of Warcraft raids like firefights in Iraq—they’re really just another handy attempt at sifting through an onslaught of data. Automated Insights’ success goes hand-in-hand with the rise of Big Data, and it makes sense that the company’s algorithms currently do best when dealing in number-based topics like sports and stocks.
On top of that, the earnings report as a journalistic form, which is what one might worry is endangered by the introduction of newsroom algorithms, is already robotically formulaic. The way the AP has been writing these reports up until now demands that human writers act like computer programs, copy-pasting the day’s numbers into their predetermined slots.
Justin Ellis spots another service employing robo-journos:
What if you could rescue your favorite saved reads by putting them into print, with one click? That’s the idea behind PaperLater, a new service that lets users create a personalized newspaper from their favorite must-reads from around the web. It’s the latest creation from the Newspaper Club, the U.K.-based company we last wrote about then it created a “robot” newspaper for The Guardian. PaperLater is a continuation of that work; the same algorithms that automatically laid out Guardian stories will now let anyone easily throw together an edition of the web’s best reads. What’s new, and what makes the service slightly more approachable to a wider audience, is a browser button for saving stories to PaperLater — and the individualized nature of single-issue printing.