ROBONEWS: Can an Algorithm Write a Better News Story Than a Human Reporter?

[Ryan Goble]

Important story about the Chicago based company Narrative Science whose tagline is "We Transform Data into Stories and Insight.™" I read the whole feature and recommend it to anyone interested in the futures of writing. Here are some interesting snippets.

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.

Read the full feature HERE.