The Rise of the AI Copy Editor

Credit: DALL-E

We all know generative AI is up-ending content creation, but how? What are people using it for, and how will specific industries be affected? FlexOS published a wide-ranging report last week that fills in many of the details of how GenAI is transforming work, showing which services and use cases are rising the quickest.

For newsrooms specifically, the report gives tacit confirmation that the role of the copy editor has been all but replaced by software. The demise of the copy editor as a career path has been happening for a long time, to be sure. My first real job in media was on the copy desk at The Edmonton Sun, and I have fond memories of late nights working with the crew on the “rim,” guarding against poorly thought-out articles and half-baked wire copy before those words were committed to permanent ink.

But the traditional copy desk is virtually extinct in today’s online media, and the report shows some of the reasons why: On its list of the most popular AI services in use across industries, Grammarly is No. 3. Now, Grammarly has been around since before the current GenAI hype cycle that began with ChatGPT, but it’s doubled down on AI-powered features since then. Anecdotally, I’ve been seeing the app’s telltale curved green arrow on screenshares in Zoom calls more often.

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While Grammarly is an excellent tool for making prose cleaner and more understandable for wider audiences, one thing it doesn’t do consistently well is find the holes in a story — the very thing copy editors excel at (the good ones, anyway). Large language models, however, can do this, too: If you ask ChatGPT for angles that you missed in a particular story, it will tell you, and it can even instantly browse the web for recent articles on the same subject to give better guidance. If your newsroom can train or fine-tune a model based on the publication’s archive, even better.

Zooming out: copy editing is just one part of the process of crafting and vetting a story. Human section editors are needed to assign, frame, and focus stories, guiding reporters as they write and research, and turn them away from blind alleys. They also need to understand the positioning of any story amongst the entirety of the publication’s coverage. But that last step that makes sure a story is edited to style and doesn’t miss any angles? Generative systems, with their ability to find patterns in information, are ideal for that.

This doesn’t have to be a pessimistic view. The progress of technology has always changed how journalism is done: Before digital, publishing used to require legions of production workers to be at the ready with PMT machines and line tape. All this progress, GenAI included, is meant to reduce the number of human tasks and effort to put the “atoms” of journalism — the new facts, the exclusive interviews, scoops of insight, and everything else — in front of an audience.

Economic realities of the media business have meant most publications — even The New York Times, which has weathered those realities better than most — have mostly done away with copy editors already, arguably before they should have. There was never going to be a return of the human copy desk, but at least now the software is up to the job.

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