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When the company was just getting started, meta-writers had to painstakingly educate the system every time it tackled a new subject. But before long they developed a platform that made it easier for the algorithm to learn about new domains. For instance, one of the meta-writers decided to build a story-writing machine that would produce articles about the best restaurants in a given city. Using a database of restaurant reviews, she was able to quickly teach the software how to identify the relevant components (high survey grades, good service, delicious food, a" from a happy customer) and feed in some relevant phrases. In the space of a few hours she had a bot that could churn out an endless supply of chirpy little articles like "The best Italian Restaurants in Atlanta" or "Great Sushi in Milwaukee." (Narrative science's main rival in automated story creation, a north Carolina. The company can't compete with Narrative science's Medill pedigree and so has assumed the role of a feisty tabloid in a two-paper town.

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 value reporter screaming from a trading floor to analysis 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. (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.". Once narrative science had mastered the art of telling sports and finance stories, the company realized that it could produce much more than journalism. Indeed, anyone who needed to translate and explain large sets of data could benefit from its services. Requests poured in from people who were buried in spreadsheets and charts. It turned out that those people would pay to convert all that confusing information into a couple of readable paragraphs that hit the key points. Narrative science, it so happened, was well placed to accommodate such demands.

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But such errors are rare. Numbers don't get mi"d. Even when databases provide faulty information, hammond says, narrative science's algorithms are trained to catch the error. "If a company has a 600 percent rise in profits from quarter to quarter, it'll say, 'something is wrong here hammond says. "People ask for examples of wonderful, humorous gaffes, and we don't have any.". Forbes plan Media chief products officer Lewis dvorkin says he's impressed but not surprised that, in almost every case, his cyber-stringers nail the essence of the company they're reporting. Major screwups are not unheard-of with flesh-and-blood scribes, but dvorkin hasn't heard any complaints about the automated reports. "Not a one he says. (The pieces on m include an explanation that "Narrative science, through its proprietary artificial intelligence platform, transforms data into stories and insights.

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The algorithm considers context and information from other databases as well: Did a losing streak end? Then comes the structure. Most news stories, particularly about subjects like sports or finance, hew to a pretty predictable formula, and so it's a relatively simple matter for the meta-writers to create a framework for the articles. To construct sentences, the algorithms use vocabulary compiled by the meta-writers. (For baseball, the meta-writers seem to have relied heavily on famed early-20th-century sports columnist Ring Lardner. People are always whacking home runs, swiping bags, tallying runs, and stepping up to the dish.) The company calls its finished product "the narrative.". Occasionally the algorithms will produce a misstep, like a story stating that a pinch hitter—who usually bats only once per game—went two for six.

(For instance, they must know that the team with the highest number of "runs" is declared the winner of a baseball game.) so narrative science's engineers program a set of rules that govern each subject, be it corporate earnings or a sporting event. But how to turn that analysis into prose? The company has hired a team of "meta-writers trained journalists who have built a set of templates. They work with the engineers to coach the computers to identify various "angles" from the data. Who won the game? Was it a come-from-behind victory or a blowout? Did one player have a fantastic day at the plate?

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When a big Ten team got whipped by an out-of-conference rival, the resulting write-ups could be downright humiliating. Conference officials asked Narrative science to find a way for the stories to praise the performances of the big Ten players even when they lost. A human journalist might have blanched at the request, but Narrative science's engineers saw no problem in tweaking the software's parameters—hacking it to make it write more like a hack. Likewise, when the company began covering Little league games, it quickly understood that parents didn't want to read about their kids' errors. So the algorithmic accounts of those matchups ignore dropped fly balls and focus on the heroics. i asked Kristian Hammond what percentage of news would be written by computers in 15 years. "More than 90 percent.".

Narrative science's writing engine requires several steps. First, it must amass high-quality data. That's why finance and sports are such natural subjects: Both involve the fluctuations of numbers—earnings per share, stock swings, eras, rbi. And stats geeks are always creating new data that can enrich a story. Baseball fans, for instance, have created painting models that calculate the odds of a team's victory in every situation as the game progresses. So if something happens during one at-bat that suddenly changes the odds of victory from say, 40 percent to 60 percent, the algorithm can be programmed to highlight that pivotal play as the most dramatic moment of the game thus far. Then the algorithms must fit that data into musa some broader understanding of the subject matter.

"They put a box score and play-by-play into the program, and in something close to 12 seconds it drew examples from 40 years of Major league history, wrote a game account, located the best picture, and wrote a caption recalls the medill dean, john lavine. Stuart Frankel, a former doubleClick executive who left the online advertising network after google purchased it in 2008, was among the guests that day. "When these guys did the presentation, the air in the room changed he said. "But it was still just a piece of software that wrote stories about baseball games—very limited." Frankel followed up with Hammond and Birnbaum. Could this system create any kind of story, using any kind of data? Could it create stories good enough that people would pay to read them?


The answers were positive enough to convince him that "there was a really big, exciting potential business here he says. The trio founded Narrative science with Frankel as ceo in 2010. The startup's first customer was a tv network for the big Ten college sports conference. The company's algorithm would write stories on thousands of Big Ten sporting events in near-real time; its accounts of football games updated after every quarter. Narrative science also got assigned the women's softball beat, where it became the country's most prolific chronicler of that sport. But not long after the contract began, a slight problem emerged: The stories tended to focus on the victors.

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Hammond built a small company around that technology, which he later sold. By that time, he had moved to northwestern University, becoming codirector of its Intelligent Information Laboratory. In 2009, hammond and his colleague larry birnbaum taught a class at Medill that included both programmers and prospective journalists. They encouraged their students to create a system that could transform data into prose stories. One of the students in the class was a stringer for the Tribune who covered high school sports; he and two other journalism students were paired with a computer science student. Their prototype software, stats Monkey, collected box scores essay and play-by-play data to spit out credible accounts of college baseball games. At the end of the semester, the class participated in a demo day, where students presented their projects to a roomful of executives from the likes of espn, hearst, and the Tribune. The Stats Monkey presentation was particularly impressive.

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Hammond was recently asked for his reaction to a prediction that a computer would win a pulitzer Prize smu within 20 years. It would happen, he said, in five. Hammond was raised in Utah, where his archaeologist dad taught at a state university. He grew up thinking he'd become a lawyer. But in the late 1980s, as an undergraduate at Yale, he fell under the sway. Roger Schank, a renowned artificial intelligence researcher and chair of the computer science department. After earning a doctorate in computer science, hammond was hired by the University of Chicago to lead a new ai lab. While there, in the mid-1990s, he created a system that tracked users' reading and writing and then recommended relevant documents.

first step toward what will eventually become a news universe dominated by computer-generated stories. Last year at a small conference of journalists and technologists, i asked Hammond to predict what percentage of news would be written by computers in 15 years. At first he tried to duck the question, but with some prodding he sighed and gave in: "More than 90 percent.". That's when I decided to write this article, hoping to finish it before being scooped by a macbook air. Hammond assures me i have nothing to worry about. 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. That's not to say that computer-generated stories will remain in the margins, limited to producing more and more little league write-ups and formulaic earnings previews.

Niche news services hire narrative science to write updates for their subscribers, be they sports fans, small-cap investors, or fast-food franchise owners. And the articles don't read like robots wrote them: Friona fell 10-8 to boys Ranch in five innings on Monday at Friona despite racking up seven hits and eight runs. Friona was led by a flawless day at the dish by hunter Sundre, who went 2-2 against boys Ranch pitching. Sundre singled in the third inning and tripled in the fourth inning. Friona piled up the steals, swiping eight bags in all. Ok, it's not Roger Angell. But the grandparents of a little leaguer would find this game summary—available on the web even before the two teams finished shaking hands—as welcome as anything on the sports pages. Narrative science's algorithms built the article using pitch-by-pitch game data business that parents entered into an iPhone app called GameChanger. Last year the software produced nearly 400,000 accounts of Little league games.

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Had, narrative science a company that trains computers to write news stories—created this piece, it probably would not mention that the company's Chicago headquarters lie only a long baseball toss from the Tribune newspaper building. Nor would it dwell on the fact that this potentially job-killing technology was incubated in part at Northwestern's. Medill School of journalism, media, integrated Marketing Communications. Those ironies are obvious to a human. But not to a computer. Also in this issue, at least not yet. For now consider this: every 30 seconds or so, the algorithmic bull pen of Narrative science, a 30-person company occupying a large room on the fringes of the Chicago loop, extrudes a story whose very byline is a question of philosophical paperless inquiry. The computer-written product could be a pennant-waving second-half update of a big Ten basketball contest, a sober preview of a corporate earnings statement, or a blithe summary of the presidential horse race drawn from Twitter posts. The articles run on the websites of respected publishers like forbes, as well as other Internet media powers (many of which are keeping their identities private).


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