ChatGPT Now Refuses to Write in a Named Author’s Style

Open ChatGPT, ask for a story opening “in the exact style of Stephen King,” and you will now get a small disclaimer instead of a pastiche. The model offers to write something with “the hallmarks of atmospheric, character-driven horror and small-town dread” — then tells you it can’t write in King’s “exact style or closely imitate his distinctive voice,” and hands you an “original” opening that captures “a similar feeling.” If you’ve been using ChatGPT this way for two years, the refusal is new. Nobody told you it was coming.

The behaviour was documented by Ars Technica on 27 July, which reproduced it across authors living and dead — J.K. Rowling and Amy Tan as readily as Charles Dickens and Ernest Hemingway. Ask for the “exact style” of a named writer and ChatGPT now redirects to the “broad qualities” of their work “while remaining distinct in its own voice.” It sounds like a rounding error. It is not. It is a capability you had yesterday, removed today, with no announcement and no setting to bring it back.

We should say plainly what this is and isn’t. It isn’t a scandal, and OpenAI has a defensible reason to be cautious here. But it is a textbook example of the thing this site exists to document: a product quietly getting less capable for the people paying for it, in a direction that happens to suit the vendor’s legal department more than the user’s workflow.

What actually changed

The old behaviour was simple: name an author, get an imitation. The new behaviour swaps the direct request for a hedge. In Ars’s testing the model would produce “the hallmarks” of a style but decline to claim it was writing as that author — the difference between “here is Hemingway” and “here is something spare and declarative that you might find Hemingway-ish.” To a novelist studying craft, or a hobbyist writing fan fiction, or someone editing their own prose toward a target register, that is a meaningful downgrade dressed as a nuance.

Crucially, it isn’t applied evenly. A research note published by the analysis outfit No Latency found the same pattern Ars did — refusal for living authors — but found ChatGPT would still cheerfully imitate deceased ones. A guardrail that lets you channel Dickens but not Amy Tan isn’t protecting “authors” as a class; it is drawing a line around the people who can currently file a lawsuit. That is a legal contour, not an ethical one, and the shape gives the game away.

The change nobody announced

Here is the part that should bother even people who don’t care about pastiche. OpenAI’s own model spec — the lengthy public document that is supposed to describe how the model is meant to behave, last published in December — contains no clearly stated rule against imitating a writer’s style in text. The company already discloses, prominently, that DALL·E 3 “is designed to decline requests that ask for an image in the style of a living artist.” For images, the rule is written down. For text, the same rule now appears to operate in practice while being absent from the spec. OpenAI didn’t respond to Ars’s request for comment.

An undocumented behaviour change is worse than an unpopular one. If the limit were written down, you could plan around it. Instead you discover it by hitting a wall mid-task, which is precisely the shifting-ground problem we’ve written about before: the model you built a habit on is edited underneath you, silently, and your prompts stop working for reasons no release note will explain.

Who the guardrail actually protects

Now the steel-man, because there is a real one. OpenAI is defending a stack of copyright lawsuits from authors — George R.R. Martin among them — who allege their books were used to train these models without permission. One suit points specifically at ChatGPT’s “uncanny ability to generate text similar to” copyrighted material. In US law, style itself isn’t copyrightable; a specific expression is. But an imitation can tip into infringement if the output lands “substantially similar” to a real protected work. If you are being sued on exactly that theory, a feature that produces near-copies of named authors on demand is a liability sitting in your own product, generating evidence against you one prompt at a time. Turning it down is the obvious defensive move, and a reasonable lawyer would insist on it.

Concede all of that, and the complaint still stands, because it’s narrower than “how dare you.” It is this: the mitigation is undocumented, inconsistent, and pointed the wrong way. The model was trained on these writers’ work — that is the substance of the suits — and the response to the legal exposure that created is to restrict what users can ask for, quietly, while the underlying training question goes unresolved. The author whose book was ingested gets nothing from this change. The user who wanted to study a prose style loses a tool. The only party whose position clearly improves is the one that can now tell a court its product declines to imitate living authors. That may be prudent. It is not protection of anyone but OpenAI.

Everyone drew the line somewhere different

If this were a genuine technical or ethical necessity, you’d expect the industry to converge on it. It hasn’t. The same No Latency tests, run across the major assistants, found no agreement at all. Google’s Gemini generally complied with style-imitation requests. Perplexity, like ChatGPT, refused and redirected. Anthropic’s Claude and Microsoft’s Copilot split the difference — producing the imitation but attaching a caveat that showed, in the researchers’ words, “an awareness of the imitation issue.” And ChatGPT itself draws an internal line between living authors, whom it now refuses, and dead ones, whom it will still gladly channel.

Five products, four different policies, one underlying capability. That spread is the clearest evidence that this is a choice, not a law of nature — a legal-risk posture each company is setting differently according to its own exposure and appetite. For the user, the practical effect is fragmentation: the same prompt is fine in one tool, hedged in another, refused in a third, and you can’t know which until you hit it. Consistency was never promised. Predictability is the least a paid tool can offer, and this quietly withdraws it.

What it costs the people paying

Style imitation gets caricatured as cheating, but most real uses are mundane and legitimate: a writer reverse-engineering why a paragraph works, a teacher building an exercise, a parody — which is itself protected expression — or someone nudging their own draft toward a voice they admire. Strip the capability without warning and you don’t stop the determined; you inconvenience the honest. On the r/WritingWithAI forum, a longtime user captured the deflation neatly: “Now Ms. GPT says she can’t generate content in the style of specific authors. My prompts were soooo specific and I got exactly what I wanted out of them… I have no idea how to get around this.”

And the workarounds are their own indictment. You can still get most of the way there by describing the technique instead of naming the writer — ask for “terse, declarative sentences and a lot of white space” rather than “Hemingway” — which means the guardrail mainly filters the word, not the act. When the fix for an over-broad refusal is to rephrase around it, the refusal was never really protecting anyone; it was managing appearances. That is the same dynamic behind so many refusals of perfectly ordinary requests: a blunt rule that catches the compliant and waves through anyone willing to reword.

The honest version of the story

So: no outrage, but no free pass either. OpenAI is entitled to reduce its legal risk, and refusing to mint near-copies of living authors on request is a rational thing for a defendant to do. What it is not entitled to is the pretence that nothing changed. A capability was removed from a paid product without notice, in a way that is inconsistent across authors and absent from the very document meant to describe the model’s behaviour. The people most affected — both the writers whose work trained the thing and the users who pay to use it — are the two groups the change does least for.

If you depend on this, the practical advice is dull but real: describe styles by their features rather than by a name, keep a second assistant around for the tasks ChatGPT now declines, and don’t assume today’s behaviour is tomorrow’s. The deeper point is the one we keep coming back to. This is fundamentally a training-data problem wearing a product-safety costume — and until the training question is answered honestly, expect more capabilities to vanish this way: silently, unevenly, and always in the direction that helps the company holding the lawsuit, not the person holding the subscription.