What happens to language when a growing amount of text published in the press, online and on social media is written by machines? This question is not just important for the profession of journalism – it also has an impact on the richness of the language we all use to comprehend, describe and discuss reality itself.
Historically, the press has been a space where public language grows and becomes richer. It is not, of course, the only driver of linguistic change, but it is one of the fields where new or emerging words, turns of phrase and ways of describing facts begin to circulate within society.
Studies on journalistic language and neologisms clearly demonstrate that newspapers are platforms for the creation and dissemination of new vocabulary, especially when it is needed to report on events, technology and social changes for a broad audience.
However, if a significant amount of journalistic writing is delegated to generative AI, this role will diminish. Large language models (LLMs) generally work by predicting the next “token” or word in a sequence. This allows them to produce fluent and believable text, but it also gives them a tendency to prioritise statistical regularity, as well as common, established arguments and formulations.
