Artificial intelligence is becoming increasingly present in everyday communication: it writes texts, translates documents, summarizes content and provides real-time responses. The result is often smooth, accurate and linguistically convincing.
Yet, it is not always reliable.
The phenomenon known as AI hallucinations originates precisely here: AI can generate grammatically perfect sentences that are inaccurate in terms of content. This happens because a language model does not truly “know” what it writes — it operates on probabilities, with a knowledge cutoff that limits the information available to it.
When data is missing, the system does not stop.
It still constructs a plausible answer.
The issue, therefore, is not the technical error itself, but the difficulty in recognizing it.
And this is where linguistic competence comes into play.
Without a genuine human-in-the-loop approach, AI can:
– produce texts that sound credible but are factually incorrect
– reinforce cultural bias
– generate representational harm
Responsible AI is not about technology.
It is about who governs the words.
Truly understanding English means going beyond formal correctness: recognizing nuances, ambiguity, double meanings, terminological choices and context. It is the difference between reading a text that “sounds right” and understanding whether what it communicates is actually correct.
In professional communication — emails, contracts, presentations, international calls — this distinction is essential. A superficial command of English can make even an incorrect message appear credible.
For this reason, artificial intelligence does not replace language study.
If anything, it makes it even more necessary.
English lessons are not only about speaking better, but about developing linguistic critical thinking: understanding what we read, evaluating what we write, and using AI as a support — not as a guide.
Because technology can suggest the words.
But only those who truly know the language can decide whether they are the right ones.
