AI Translation Bias: Why Human Translators Matter
AI translation promises to flawlessly bridge languages, but the outputs it generates often carry hidden biases. Without the human touch, the assumptions it spits out can twist meaning and marginalise voices, raising urgent questions about who gets heard when machines speak for us.
AI translation tools rely on massive datasets and complex machine learning algorithms to convert text across languages. These datasets are often sourced from the internet, where certain voices – particularly those of dominant cultural groups – are overrepresented, reflecting historical and social biases. As a result, machine-generated translations can often reproduce harmful stereotypes, discriminatory language or culturally skewed perspectives.
The silent ‘she’
Gender bias in AI translation often reflects and reinforces societal stereotypes, especially when translating from and into languages with grammatical gender. When translating into German, for example – a language that has actively worked towards gender-inclusive language in recent years – AI systems frequently fail to use these inclusive forms. When dealing with plurals – one example being the word ‘students’ – AI tends to translate with the generic masculine noun Studenten instead of either adding the ‘*innen’ ending (Student*innen), which includes women or seeking a gender-neutral alternative, such as Studierende (literally meaning ‘those who study,’ but a very common term for students in everyday German). In languages such as French, Spanish and Italian – which have gendered versions of the word ‘everybody’ – AI translations again often only use the masculine version, rather than using both masculine and feminine: toutes et tous, todas y todos or tutti e tutte. These inclusive forms are commonly used in official writing and omitting the female form could be seen as deliberately offensive and exclusionary of women and non-binary people.
Encoded allegiances
Much like gender bias, geopolitical bias in AI translation can also have serious implications, as even one word can carry deep political and cultural meaning. For instance, whether an AI system writes Kyiv or Kiev reflects a political stance: Kyiv aligns with the Ukrainian government’s preferred spelling, asserting independence from Russian influence, while Kiev reflects the older Russian-based spelling. In light of Russia’s full-scale invasion of Ukraine, the choice of spelling can carry political significance. The issue of geopolitical bias becomes even more visible in AI systems like the Chinese-developed DeepSeek, which refers to Taiwan as part of China and censors certain topics. In my own experiments, when asked about what happened in 1989 at Tiananmen Square, DeepSeek claimed a system error, before blocking me from the system altogether. Such examples show that AI models are shaped by the political and cultural biases of their creators. Unlike a human translator – who can be instructed to follow specific stylistic or ethical choices – AI translation leaves users with little control and its linguistic choices, though seemingly a difference of mere letters, in fact make the difference between respect and deep cultural offence.
Lost in dialect
AI translation systems also struggle significantly with regional dialects, often rendering them as broken or incorrect versions of the standard language rather than treating them as distinct, legitimate linguistic varieties. This can be problematic because it implies that dialect speakers are simply “failing” to use the standard language, rather than expressing a valid regional identity. AI does not truly understand dialects or the cultural context they carry. Its errors can erase the richness and identity embedded in regional speech, as well as simply producing incoherent translations.
Some may assume that AI provides objective, neutral translations, but language is never neutral – it is shaped by culture, power and context. AI-generated translations do more than translate – they interpret, filter and reshape meaning in ways that reflect cultural and institutional power structures. True linguistic inclusivity requires awareness, human oversight and understanding of the social and political weight every word carries. Every text deserves the care and understanding that only a human translator can provide. Peschel Communications has been providing expert translations by native speakers for over 25 years, bringing linguistic nuance and cultural understanding to every translation.
