A Chicago startup called Narrative Science makes scripts that turn raw data feeds such as seismological data or website analytics into accessible natural language reports. Some news outlets are already using them to get out earthquake and Little Leagues baseball reports quickly and cheaply.
The founder, Kristian Hammond, has big ideas. "Pulitzer Prize by 2017." "90% of news written by bots in 2030."
This TL;DR was written by a human. Just saying.
- The LA Times claims they were first to publish anything on the quake, and outside the USGS, they probably were.
- The LA Times example isn’t special because it’s the first algorithm to write a story on a major news site.
- Indeed, Kristian Hammond, cofounder and CTO of Narrative Science, thinks some 90% of the news could be written by computers by 2030.
- The LA Times earthquake story, written by an algorithm created by one of their staff, included a disclaimer.
This TL;DR was written by a bot.
I mistakenly wrote "Bill Hammond" instead of "Kristian Hammond" in my TL;DR. (Sorry Kristian.)
But this isn't the first bot that the LA Times has operated either. Folks like Ben Welsh (who works at the LA Times, and did this awesome lightning talk: http://www.youtube.com/watch?v=iP-On8PzEy8 ) and Matt Waite (who won a Pulitzer Prize for Politifact & now teaches at University of Nebraska Lincoln) have also been writing bots to help with the reporting process (and yes in some case actually generate copy) for years.
Narrative Science certainly was not the first or only group to do this.
If the data is already machine-readable, in many instances, what I want to see are a few slices through the database and a few visualizations. What I don't want is a big text blob that must first be piped through my brain to re-extract the information.