When ChatGPT showed how easy it was to write an "original" academic paper that could get a passing grade, the need for some kind of AI detector was suddenly starkly clear. The market quickly responded, and GPTZero, created by 23-year-old Edward Tian, was an overnight sensation last spring. College professors now routinely check papers for AI authorship.
In the media world, the need for such a tool was perhaps less urgent, since editors tend to have a tighter grip on how copy is produced, and few writers would risk their reputations trying to pass off synthetic articles as their own. That is, until the boondoggle with Sports Illustrated, where articles supplied by a third party appeared to have been written by AI (note: the company that supplied the articles claims they were human-written).
The incident got widespread attention, and it underscored the need for AI detection in media, especially when you publish content at scale, from multiple sources. Even if your in-house editorial team is strictly human-driven, freelancers and syndication partners may not have gotten the memo.
So do managing editors need to add "copy and paste article into AI detector" to the long list of editors' duties? They can, but another solution may be to build it into existing processes and tools, which is exactly why Copyleaks exists. The company began as a plagiarism detector and now markets itself as an AI detection company. It claims to be able to do detect synthetic text across models, in multiple languages, and in detail (i.e. showing which parts of a document are AI generated, as opposed to a simple Yes/No result).
Lee Gaul is the enterprise sales director at Copyleaks, and he's this week's guest on The Media Copilot podcast. Our conversation goes beyond simple AI detection and explores the big-picture issues driving the demand for the service as well as the increased need for human judgment when machines enter the picture.
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Sniffing Out AI Writers, With Lee Gaul