Can AI Write Creatively? It Depends Who’s Reading.

Back in March, we published this piece by Rhea Purohit in response to Sam Altman’s tweet about an unreleased OpenAI model that impressed him with its creative writing. Now that GPT-5 is out, it’s unclear whether that mysterious LLM was GPT-5 itself or something else that never saw the light of day. What endures, though, is the deeper question Altman’s tweet raised—whether AI can truly be creative. It’s a question the late cognitive scientist Margaret Boden spent decades exploring, long before ChatGPT made the topic mainstream. Her passing last month makes revisiting these ideas feel all the more timely.—Kate Lee

Was this newsletter forwarded to you? Sign up to get it in your inbox.

Sam Altman recently tweeted that OpenAI has trained a model that’s good at creative writing, asserting that it was the first time he’d been “really struck by something written by AI.” While the unnamed model isn’t publicly available yet, Altman gave us a glimpse of its potential by sharing a prompt—“please write a metafictional literary short story about AI and grief”—alongside the 1,172-word narrative it generated.

Reactions to Altman’s tweet were mixed—some were deeply moved by the AI’s story, while others dismissed it as trash. But I think debating the literary merit of the piece misses the point. The model’s demo begs a deeper question: Are large language models capable of writing creatively?

When we judge whether AI can write creatively, we’re really expressing our own beliefs about what creativity is—not something many of us spend much time thinking about. We may think we know it when we see it, but putting “it” into words is surprisingly difficult. Is originality an illusion, a deft trick of taking in data about the world and parsing and rearranging it? Or is it rooted in some ineffable aspect of human experience? Or is it something else entirely: a subjective judgment that’s open to interpretation by whomever is interacting with the creative work?

As I tried to get to the bottom of these questions, I found a bunch of fascinating ideas about how creativity might work in machines. One thing I did not find is a black-or-white answer to the question of whether LLMs are our next great literary talent. It turns out it depends a lot on how we, the humans in this story, look at things.

Machines and theories of creativity

More than two decades before Altman’s tweet, cognitive scientist Margaret Boden published a paper on creativity and artificial intelligence. Boden theorized that creativity came in three broad types: “combinational” creativity, improbably combining familiar ideas (a chef who prepares dishes that are a fusion of Spanish and Thai cuisines); “exploratory” creativity, discovering new ideas within a familiar conceptual space (a chef at the cutting edge of contemporary Spanish food); and “transformational” creativity, changing some dimension of a familiar space so that new structures can arise (a chef reimagining what constitutes food).

Boden cited an early instance of AI demonstrating combinational creativity: a computer program called the Joke Analysis and Production Engine that was programmed to generate riddles with puns like: “What kind of murderer has fiber? A cereal killer,” and “What do you call a depressed train? A low-comotive.” However, Boden said that computer programs of that era had been most successful in exploratory creativity, and that the transformational kind remained a distant dream.