A Controversial Technology Is Making Me a Worse Writer. No, Not That One.

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I wrote this article. I am sure of it not because I remember writing this thing in fits and starts throughout Saturday, but because an A.I. detector called Pangram blessed these paragraphs with a “100% Human Written” score. Thank heavens.

An A.I. detector’s value proposition is simple enough. For a teacher, it ensures that students’ work is their own. For the rest of us, it functions to preserve our last shreds of shared reality at a time of rapidly developing make-stuff-up machines. However, the accuracy of detectors is the subject of reasonable debate. University of Chicago researchers and a New York Times journalist have found Pangram, one of the buzziest and most popular A.I. detectors, to operate excellently . The company has made claims about its accuracy that strain my own credulity; a Pangram blog post last year stated that it had a “1 in 10,000 false positive rate.”

I’ve found a far higher error rate in my own unscientific testing. Tech writer Alex Heath, who uses A.I. in a back-and-forth process with his own tweaking, explained recently that Pangram judged his text to be 100 percent human. I suspect that the detector would flag the most uninvolved “Write this for me” slop but not the text that involves a lot of human molding . As writer Freddie deBoer argues, Pangram doesn’t seem broken but does seem easy to break .

Whatever the future holds for the accuracy of A.I. detectors, I am unsettled by what both the A.I. writing and the detectors are doing to me right now. I worry about how A.I. writing and efforts to sniff it out are changing fully human writing. I write all week, every week, and can feel this story’s arsonists (LLMs, particularly when used the wrong way) and firefighters (A.I. detectors) weighing on my process in negative ways.

Like many journalists, my writing style comes from the books, news articles, blogs, and (yes) social media posts that have latched on to my brain over the years. A.I. writing is now in my water supply, whether I can identify each new gulp or not. It feels inevitable that I’ve started to internalize its ticks, even the most infamous ones, like incessant em-dashing and overreliance on the “It’s not x but y ” structure. For one thing, I fear this will make me a worse writer, dragging a talent that was good enough to get me hired here (and elsewhere!) back toward the A.I.-generated median. Scarier yet, it’s possible that someone—or, heaven forbid, some A.I. detector—might mistake my text for ChatGPT’s.

I have started to self-police against this outcome. A few times lately, I’ve caught myself modifying my own work to sound “less like A.I.” In the process, I’ve probably picked words I wouldn’t have settled on otherwise. It feels dystopian—and I doubt I’ve succeeded. One thing LLMs are great at is rapidly finding little acorns within huge blocks of text.