Localization

Recipe localization looks like an easy prompt. “Create a Jamaican version of Moroccan couscous.” The model smiles politely, throws in jerk seasoning, allspice, scotch bonnet, maybe coconut milk if it is feeling ambitious, and returns something that looks country-specific enough to survive a quick marketing review. The title says “Jamaican.” The ingredients sound Jamaican. The format is clean. No hallucinated oven temperature from another dimension. Excellent, ship it. ...

TL;DR for operators The paper does not merely say that GPT-generated stories contain national clichés. That would be mildly interesting, in the way that discovering a tourist brochure likes sunsets is mildly interesting. The sharper finding is structural. When Rettberg and Wigers prompted gpt-4o-mini to write 1,500-word “potential” stories for 236 demonyms, the model produced surface diversity—olive trees, fjords, forests, trains, village elders, festivals—but repeatedly returned to the same basic narrative machine: someone comes back to a small town or village, discovers that community or tradition has weakened, organises a symbolic event, and restores harmony.1 ...