You Ask, I Answer: Stopping AI Americanisms?

In today's episode, Nigel asks, how do I stop AI from using American spelling and culturalisms? This is a pretty big problem. There was an article not too long ago in The Guardian that showed linguistic analysis of the speeches delivered by the ministers of parliament in the UK and in England and how American American language traits were rapidly creeping into the speeches that MPs were giving from the floor of parliament because they were using generative AI to generate their speeches and then just reading them aloud. We'll not discuss politics on this episode as to whether or not that's even a good idea, but there's a couple different ways to handle this. The first is um make sure that whatever tool you're using, that the interface supports the variant of English that you want to be using because AI is absolutely trained on global amounts of language, but the English language that is available tends to be slanted towards American English.

That's number one. Number two is make sure that you are using reasoning models. So reasoning models are models that do thinking. This is GPT 5.2, uh high or extra high. Gemini 3 Pro and Flash with thinking turned on.

This is Claude Opus with extended thinking turned on. This is Deep Seek R1. This is Alibaba Quen 3. All these models have thinking capabilities, which means that they can essentially effectively do a rough draft. All of these models have different ways of implementing their reasoning.

This is something that is a fairly technical subject in terms of things like Mobicala tree search or reinforcer modeling, PRMs or backtracking. But they all work really well with something with what is called checklist monitoring. You tell AI in your prompt to build a checklist of the tasks you want it to do, or you just write a checklist as your prompt. And then using a thinking model to validate the its results at the end. Now here's the thing that is challenging for a lot of people, humans.

You can't tell AI, don't do this. If you say don't think of an elephant, think of a dog. So you would not say, don't use American English or American cultural references. Use Welsh references, use Welsh spelling, use Scots Gaelic, you know, you whatever the thing is that you want it to do, you have to explicitly declare it and say, this is what you should be doing. So if you notice certain Americanisms in the writing, even you would not just say don't do this, you would say don't do this, do this instead.

Don't do this, do this instead. And if you combine that with a checklist-based prompt, then when the model thinks through, gets to that point in the process, it will look up a checklist and go, oh, I did this, I should do this instead. Or I did this, I should do this instead. It's like delegating to an intern. But it works with all three major kinds of reasoning models that are out there.

Backtracking PRMs in the MCPS. So that you get more of what you want. Did you tell it what to use instead? You not just say don't do this, say do this instead, use an N-dash instead, and make sure there's a space on the other side. And incorporate into the logic of your prompt so the reasoning model can checklist it and say, Yes, I did this thing, or no, I did not do this thing, let me go back and fix it.

That's how you get it to stop doing certain behaviors. It's never enough to say don't do this. You have to give it explicitly what you want it to do instead, just like an intern. So, I hope that was helpful. Thanks for the question.

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