Generative artificial intelligence (AI) tools are more widespread than ever, and one of the functions they offer is fast, real-time translation. Some people are even questioning the need to ever learn another language, if near-instant translation is so widely available to all of us, often for free.

However, those translations are far from perfect. While AI translations are very fluent, fluency doesn’t equal accuracy. Even proficient bilinguals can overlook errors hidden under the surface.

Some of the mistakes in AI translation come from a lack of learning data, insufficient prompts, or even hallucations – confident presentation of false information, a hallmark of AI chatbots.

Other errors reflect something more fundamental: the inherent complexity and flexibility of human language, and the linguistic or cultural differences between two languages.

In my professional work reviewing real AI translations between English and Chinese, I have found some revealing examples of this problem. English and Chinese are two of the most used languages, with a large amount of data for AI to learn from; the issues could be more serious if you’re working on less common languages.

For those using generative AI to translate, it’s important to keep these risks in mind.

Where can AI translation go wrong?

Words can have multiple meanings and AI may not always choose the right one.

In one translation I reviewed, an international student described Australian professors as laid back because they wore thongs to class. AI interpreted “thongs” as G-strings (underwear) rather than flip-flops........

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