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The Impact of AI on Human Translation: Collaboration or Competition?

Author: Mona Knöttner


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Nowadays, millions of people are using Google Translate, ChatGPT, and DeepL. Simple translation tools have developed into unexpectedly useful assistants for school, work and travel. The Google Translate app, for example, has exceeded 1billion installs since 2021. This popularity has led to a significant question: will AI take the place of human translators? Let’s take a look at the history and future of AI translation.


The Rise of AI-Powered Translation


AI translation was already developed in the 1950s. At that time, translation systems were based on hand-coded language rules and didn’t work quite well. In the late 1980s, computer-based translation improved with the introduction of statistical machine translation. This early form of AI translation generated texts by usinglarge databases.


Neural Machine Translation


Neural machine translation was introduced in 2010. Hereby, machine learning and neural networks provide translations that are far more accurate and natural. Today, AI translation based on neural networks is now commonly used in both daily situations and professional environments.


Strengths and Weaknesses


At present, in 2025, companies must make a choice between hiring human translators or blindly trusting AI. Professional human translators continue to perform by about 18% better than machines. In texts where idioms, culturally specific terms, and guidelines need to be considered, human translators are essential. But when it comes to translating lots of similar content, neural machine translation actually holds up pretty well.


Translation Costs


Although human translation produces highly accurate content, it is the most expensive form of translation, costing $0.12 per word. The cost of machine translation services is around $0.05 per word. So, what’s the catch? Computer-based translations are often inaccurate, and cultural awareness is still missing.


From Competition to Collaboration


The role of the translator has changed due to frequently developing technology. But despite its risk to the translation industry, AI has become a useful tool. CAT tools, for example, enable consistency in translations with AI-powered translation memory. Moreover, Machine Translation Post-Editing, or MTPE, has become an important partof a translator's job.


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Why Context Can’t Be Ignored in Translation


Although machine translation is quick and effective, it overlooks cultural nuances and context. Post-editors can help with that. High-quality content requires an understanding of context, including cultural backgrounds, grammatical rules, and idioms that are sometimes impossible to translate. AI is still unable to imitate these human abilities.


Ethical and Professional Implications


Despite the many advantages to AI translation, it is also important to consider how it affects ethics. A major concern is that when AI generates texts, it ignores gender bias and stereotypes. Additionally, since machines cannot be held accountable for errors, copywriters must carefully examine AI translations before publishing the translated text.


How Universities Are Preparing Future Translators


The translation industry and its job market have been facing fundamental changes caused by new technology. Many universities are already adjusting to these rapidchanges since job security is a major concern. For example, a new course focused on AI translation has been introduced by the UK's Institute of Translation and Interpreting.


The Future of AI Translation


So, what will the future of translation look like? What changes can we expect in the next five to ten years? The truth is, we don’t know for sure. However, we already do know that technologies like quantum computing will impact the development of AI translation. Still, despite these technological developments, human-AI cooperation will be necessary in the future.


Conclusion


In the end, translation is more important than ever as the world becomes more connected. AI has definitely made things faster and easier, but we still need human experts for copyright, cultural nuances, and accuracy. In the future, good translation will result from human translators and technology working together.


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