Scoopfeeds — Intelligent news, curated.
What AI’s Style Tells Us About It
publications

What AI’s Style Tells Us About It

The Atlantic · Jun 15, 2026, 11:00 AM

In the late 19th century, it was commonly believed that a criminal or lunatic could be recognized at a glance, based on certain physiognomic tells. “Enormous jaws, high cheek-bones,” and other animal-like features, the influential criminologist Cesare Lombroso wrote, were signs of an “irresistible craving for evil for its own sake.” Today, savvy readers use a similar approach to identify AI writing, by hunting for supposed telltale signs. The em dash and the “it’s not X; it’s Y” construction are the prognathous jaw of the large language model, betraying its hidden inhumanity.The problem, in both cases, is that you can’t always deduce what’s inside from what’s outside. A person might have rough features and a kind heart, just as a writer might use em dashes despite being human. It’s not a giveaway—it’s a style choice. (See?) And as AI models evolve, their ability to mimic human writing is sure to improve. People have reportedly begun to make deliberate spelling errors to show that they are not chatbots; it’s only a matter of time before the chatbots learn to follow suit.To see what’s distinctive about AI writing, you have to look deeper than quirks of spelling or syntax. Every writer has a style—a set of preferences and preoccupations that reveals how they experience the world. Jane Austen and Charles Dickens were both masters of comedy, but the contrast between her ironic understatement and his histrionic exaggeration reflects profoundly different personalities and life experiences, in which class and gender played an important part.[Jasmine Sun: The human skill that eludes AI]If, as a French saying has it, “style is the man himself,” what does the style of AI writing tell us about it? For one thing, it has no fixed style, revealing that it has no fixed self. It’s happy to burn tokens saying the same thing in as many ways as you want. LLMs generate writing probabilistically: After training on billions of texts, they build complex equations to predict which words are

Article preview — originally published by The Atlantic. Full story at the source.
Read full story on The Atlantic → More top stories
Aggregated and edited by the Scoop newsroom. We surface news from The Atlantic alongside other reporting so you can compare coverage in one place. Editorial policy · Corrections · About Scoop