From newsgathering to the production and distribution of news and information, AI is behind more and more tools used by newsrooms worldwide. To find out more about the most recent AI developments for journalism and how newsrooms are adapting to these new technologies, we spoke with three top newsroom managers from the Associated Press, Bloomberg, and the Financial Times, as part of the 2020 JournalismAI Festival. Here’s what they had to say.
The important thing is figuring out how to release your journalists from having to do the mundane tasks so that they can focus on the high-value projects that people come to us for. That’s really the sweet spot of AI at the moment.
AI has improved the efficiency of operations at Bloomberg, the FT, and the AP through a combination of revenue-driving and production-oriented initiatives. Some examples:
Emma V. O’Brian – Chief of Staff for Breaking News & Markets – explained how Bloomberg piloted a bot that alerts editors via Slack of demographic discrepancies among sources quoted in the articles;
Cait O’Riordan – Chief Product and Information Officer – shared how the FT’s designated Product and Information team collaborates with journalists in the editorial department on a series of innovative projects;
Lisa Gibbs – Director of News Partnerships & AI News Lead – explained how the AP has managed to improve production efficiency via automated transcription, summary tools, and story templates.
For media organisations, the endgame of incorporating AI into business models is to compete against advertising heavyweights like Facebook and Twitter for audience attention. News organisations like the Financial Times can’t pay engineers as much as the tech giants can, but they can implement AI technology to take up time-consuming tasks, thus freeing up journalists to produce the kind of investigative work that holds power to account and raises the organisation’s profile.
Journalists need to develop some degree of competency in data science to remain competitive as AI becomes more prevalent in larger newsrooms. From the AP to Bloomberg, there is a growing expectation in media organisations that prospective hires have some background in computer science and are comfortable collaborating with engineers.
Smaller news organisations must abandon increasingly vulnerable ad-based models for more stable subscription models before they can consider engaging with machine learning. Despite their relative success with these technologies, most larger news organisations don’t have an actionable template for introducing AI into the newsroom but emphasise the value of determining what problems need solving and where these technologies might fit into the process.
The job titles of the three speakers did not exist in newsrooms even five years ago. Their work bridges the realms of product development, editorial, and engineering, and each one of them has been charged with shepherding a major media organisation through the murky waters of digital-first journalism. As a growing number of newsrooms start incorporating machine learning into their business, our experts outline the risks of putting the cart before the horse – from allowing the allure of AI to outshine the need for its results-driven implementation, to overlooking the resource-heavy troubleshooting that these technologies demand. Their work also highlights the eye-opening potential of AI for journalism, from relieving journalists of time-consuming busywork to raising newsroom standards of inclusion and representation.
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This article was written by Mara Veitch, POLIS intern and LSE’s MSc student.