Programming The News: The Future Of Reporting Is Algorithms

Predictions

from the I-for-one-welcome-our-new-fedora-clad-robotic-overlords dept

This may seem like the sort of statement usually delivered by an overblown narrator as rockets and lasers go zooming* by, but here goes: In the world of journalism, the future is now! Granted, it’s the kind of future that often makes waves in the present and raises at least as many questions as it answers, but if you wanted a bright, problem-free future, you’d have to travel back to the divergence point somewhere between Philip K. Dick and The Jetsons… and then eliminate the dystopians.

*Yes, I realize lasers don’t make noise or “zoom” by, but that hasn’t prevented George Lucas from becoming insanely rich, has it?

But you can’t, so here we are, discussing journalism… by robots! [INS FANFARE/LASER NOISES]

Journalist Ken Schwencke has occasionally awakened in the morning to find his byline atop a news story he didn’t write.

No, it’s not that his employer, The Los Angeles Times, is accidentally putting his name atop other writers’ articles. Instead, it’s a reflection that Schwencke, digital editor at the respected U.S. newspaper, wrote an algorithm — that then wrote the story for him.

Instead of personally composing the pieces, Schwencke developed a set of step-by-step instructions that can take a stream of data — this particular algorithm works with earthquake statistics, since he lives in California — compile the data into a pre-determined structure, then format it for publication.

His fingers never have to touch a keyboard; he doesn’t have to look at a computer screen. He can be sleeping soundly when the story writes itself.

This isn’t exactly new news. (Then again, neither is the morning paper, but that’s a discussion for another time…) Algorithmic story generation has been around for a few years now, with Narrative Science leading the field. A couple of years ago, Narrative Science was the story, rather than just the automated recap. George Washington University’s website had covered a GWU baseball game with a longish recap that only got around to mentioning the opposing pitcher’s perfect game in the seventh (out of eight) paragraph. Speculators wondered if a bot was behind this “ignoring the forest for the trees” recap. Narrative Science’s techies were highly offended and responded by producing two algorithmically-generated recaps — one from the home team POV and a more neutral piece.

The first concern with robo-journalism is often expressed by the journalists themselves: are we getting pushed out?

Kristian Hammond, co-founder of Narrative Science, doesn’t see it that way.

This robonews tsunami, he insists, will not wash away the remaining human reporters who still collect paychecks. Instead the universe of newswriting will expand dramatically, as computers mine vast troves of data to produce ultracheap, totally readable accounts of events, trends, and developments that no journalist is currently covering.

This is somewhat echoed by L.A. Times reporter Schwencke, who sees the algorithmic output as a boon for busy journalists.

Schwencke says the use of algorithms on routine news tasks frees up professional reporters to make phone calls, do actual interviews, or dig through sophisticated reports and complex data, instead of compiling basic information such as dates, times and locations.

“It lightens the load for everybody involved,” he said.

Schwenke’s “bot” is rather simple, functioning best with a limited dataset and a minimum of formatting. Narrative Science’s output is a bit more complex, allowing customers to adjust the “slant” of the generated stories. Not only that, but the software can cop an attitude, if requested.

The Narrative Science team also lets clients customize the tone of the stories. “You can get anything, from something that sounds like a breathless financial reporter screaming from a trading floor to a dry sell-side researcher pedantically walking you through it,” says Jonathan Morris, COO of a financial analysis firm called Data Explorers, which set up a securities newswire using Narrative Science technology. (Morris ordered up the tone of a well-educated, straightforward financial newswire journalist.) Other clients favor bloggy snarkiness. “It’s no more difficult to write an irreverent story than it is to write a straightforward, AP-style story,” says Larry Adams, Narrative Science’s VP of product. “We could cover the stock market in the style of Mike Royko.”

This leads to the ethical quandary presented by the use of bots. Is robo-generated journalism really journalism, and is the use of algorithms a betrayal of readers’ trust, especially when a familiar name is on the byline? If factual errors are discovered, does the blame lie with the software, or with the journalist who agreed to let the article “write itself?”

The answer here isn’t simple (and the question likely isn’t even fully formed yet), but the key is transparency.

“People are already reading automated data reports that come to them, and they don’t think anything of it,” said Ben Welsh, a colleague of Schwencke’s at the Times.

Welsh says that responsibility for accuracy falls where it always has: with publications, and with individual journalists.

“The key thing is just to be honest and transparent with your readers, like always,” he said. “I think that whether you write the code that writes the news or you write it yourself, the rules are still the same.”

“You need to respect your reader. You need to be transparent with them, you need to be as truthful as you can… all the fundamentals of journalism just remain the same.”

Questions involving intellectual property are also raised, although they aren’t discussed in these articles. Who holds the copyright on the generated articles? In Schwencke’s case, these rights are likely retained by the L.A. Times. In the case of Narrative Science, it’s probably defined by contractual terms with the end user. Once the contract is up, the generated articles’ copyright reverts to the end user.

Schwencke’s homebrewed algorithm is a different IP animal. If he switches papers, does he retain the right to the “bot?” Or is that algorithm, developed while employed with the L.A. Times, considered a “work for hire,” and thus, the paper’s property? Arguably, his algorithm is an extension of him, covering his area of expertise and designed to emulate his reporting. What if Schwencke generates a similar piece of software for his new employer? Would he be permitted to do this, or would this be prevented by additions to “non-compete” clauses? Is it patentable?

The more ubiquitous “robo-journalism” becomes, the more issues like these will arise. Hopefully, IP turf wars will remain at a minimum, allowing for the expansion of this promising addition to the journalist’s toolset. With bots handling basic reporting, journalists should be freed up to pursue the sort of journalism you can’t expect an algorithm to handle — longform, investigative, etc. This is good news for readers, even if they may find themselves a little unnerved (at first) by the journalistic uncanny valley.

Filed Under: algorithms, journalism, programming the news
Companies: la times, narrative science