Posted on 07/11/2012 5:27:22 PM PDT by Hunton Peck
The new reporter on the US media scene takes no coffee breaks, churns out articles at lightning speed, and has no pension plan.
That's because the reporter is not a person, but a computer algorithm, honed to translate raw data such as corporate earnings reports and previews or sports statistics into readable prose.
Algorithms are producing a growing number of articles for newspapers and websites, such as this one produced by Narrative Science:
"Wall Street is high on Wells Fargo, expecting it to report earnings that are up 15.7 percent from a year ago when it reports its second quarter earnings on Friday, July 13, 2012," said the article on Forbes.com.
While computers cannot parse the subtleties of each story, they can take vast amounts of raw data and turn it into what passes for news, analysts say.
"This can work for anything that is basic and formulaic," says Ken Doctor, an analyst with the media research firm Outsell.
And with media companies under intense financial pressure, the move to automate some news production "does speak directly to the rebuilding of the cost economics of journalism," said Doctor.
Stephen Doig, a journalism professor at Arizona State University who has used computer systems to sift through data which is then provided to reporters, said the new computer-generated writing is a logical next step.
"I don't have a philosophical objection to that kind of writing being outsourced to a computer, if the reporter who would have been writing it could use the time for something more interesting," Doig said.
Scott Frederick, chief operating officer of Automated Insights, another firm in the sector, said he sees this as "the next generation of content creation."
The company got its start in 2007 as StatSheet, which generates news stories from raw feeds of play-by-play data...
(Excerpt) Read more at ca.news.yahoo.com ...
(But the very word is silly; as everybody knows, al Gore ain't got no rhythm.)
So you could code the program for viewpoint bias, as well - leftist, environmentalist, socialist, etc. The MSM could save a lot of money and keep its one sided slant, at the same time. It would sure save time rewriting history too.
And yes, algorithms can know (in general) what people are thinking in response to a news article, because they can monitor twitter and facebook and other places for instant feedback to an event. And if people aren't talking about it correctly, it wouldn't be that hard to keep adjusting it until they get the feedback they are programmed for.
New York Times articles are especially easy. Just insert adjectives and adverbs from one of three lists: Conservative (incendiary, shopworn, mean-spirited, etc.), Liberal (subtle, nuanced, thoughtful...), and Republican Maverick (bold, independent, courageous...). They already pretty much write themselves.
Yikes... creepy indeed.
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