Given that an entire afternoon was dedicated to a “Robot Journalism Bootcamp” at the Global Editors Network Summit this week, it’s probably safe to say that automated journalism has finally gone mainstream — hey it’s only taken close to 40 years since the first story writing algorithm was created at Yale. But there are still lots of ethical questions and debates that we need to sort out, from source transparency to corrections policies for bots. Part of that hinges on exactly how these auto-writing algorithms work: What are their limitations and how might we design them to be more value-sensitive to journalism?
Despite the proprietary nature of most robot journalists, the great thing about patents is that they’re public. And patents have been granted to several major players in the robo-journalism space already, including Narrative Science, Automated Insights, and Yseop, making their algorithms just a little bit less opaque in terms of how they operate. More patents are in the pipeline from both heavy weights like CBS Interactive, and start-ups like Fantasy Journalist. So how does a robo-writer from Narrative Science really work?
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