Can an Algorithm Write a Better News Story Than a Human Reporter?
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. 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 quote 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 company founded as Stat Sheets, has broadened its mission in similar fashion. 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. It too got its start in sports, writing accounts of Major League and big-college games as well as creating a trash-talk generator called StatSmack. After realizing that turning data into stories presented an opportunity far larger than sports, the company changed its name to Automated Insights. “I used to put limitations on what we do, assuming our stories would be specific to data-rich industries,” founder Robbie Allen says. “Now I think ultimately the sky is the limit.”)
And the subject matter keeps getting more diverse. Narrative Science was hired by a fast-food company to write a monthly report for its franchise operators that analyzes sales figures, compares them to regional peers, and suggests particular menu items to push. What’s more, the low cost of transforming data into stories makes it practical to write even for an audience of one. Narrative Science is looking into producing personalized 401(k) financial reports and synopses of World of Warcraft sessions—players could get a recap after a big raid that would read as if an embedded journalist had accompanied their guild. “The Internet generates more numbers than anything that we’ve ever seen. And this is a company that turns numbers into words,” says former DoubleClick CEO David Rosenblatt, who sits on Narrative Science’s board. “Narrative Science needs to exist. The journalism might be only the sizzle—the steak might be management reports.”
For now, though, journalism remains at the company’s core. And like any cub reporter, Narrative Science has dreams of glory—to identify and break big stories. To do that, it will have to invest in sophisticated machine-learning and data-mining technologies. It will also have to get deeper into the business of understanding natural language, which would allow it to access information and events that can’t be expressed in a spreadsheet. It already does a little of that. “In the financial world, we’re reading headlines,” Hammond says. “We can identify if some company’s stock gets upgraded or downgraded, somebody gets fired or hired, somebody’s thinking of a merger, and we know the relationship between those events and a stock price.” Hammond would like to see his company’s college sports stories include nonstatistical information like player injuries or legal problems.
But even if Narrative Science never does learn to produce Pulitzer-level scoops with the icy linguistic precision of Joan Didion, it will still capitalize on the fact that more and more of our lives and our world is being converted into data. For example, over the past few years, Major League Baseball has spent millions of dollars to install an elaborate system of hi-res cameras and powerful sensors to measure nearly every event that’s occurring on its fields: the velocities and trajectories of pitches, tracked to fractions of inches. Where the fielders stand at any given moment. How far the shortstop moves to dive for a ground ball. Sometimes the real story of the game may lie within that data. Maybe the manager failed to detect that a pitcher was showing signs of exhaustion several batters before an opponent’s game-winning hit. Maybe a shortstop’s extended reach prevented six hits. This is stuff that even an experienced beat writer might miss. But not an algorithm.
Hammond believes that as Narrative Science grows, its stories will go higher up the journalism food chain—from commodity news to explanatory journalism and, ultimately, detailed long-form articles. Maybe at some point, humans and algorithms will collaborate, with each partner playing to its strength. Computers, with their flawless memories and ability to access data, might act as legmen to human writers. Or vice versa, human reporters might interview subjects and pick up stray details—and then send them to a computer that writes it all up. As the computers get more accomplished and have access to more and more data, their limitations as storytellers will fall away. It might take a while, but eventually even a story like this one could be produced without, well, me. “Humans are unbelievably rich and complex, but they are machines,” Hammond says. “In 20 years, there will be no area in which Narrative Science doesn’t write stories.”
For now, however, Hammond tries to reassure journalists that he’s not trying to kick them when they’re down. He tells a story about a party he attended with his wife, who’s the marketing director at Chicago’s fabled Second City improv club. He found himself in conversation with a well-known local theater critic, who asked about Hammond’s business. As Hammond explained what he did, the critic became agitated. Times are tough enough in journalism, he said, and now you’re going to replace writers with robots?
“I just looked at him,” Hammond recalls, “and asked him: Have you ever seen a reporter at a Little League game? That’s the most important thing about us. Nobody has lost a single job because of us.”
At least not yet.
Senior writer Steven Levy ([email protected]) interviewed Amazon’s Jeff
Bezos for issue 19.12.
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