Today, the rules of the game in the translation industry are being changed by artificial intelligence and the automation of key processes, including neural machine translation (NMT), thanks to the ability to quickly translate large volumes of text while preserving the original meaning. Will technology completely replace the experience and expertise of translators?
How technology has affected the translation industry?
In recent years, artificial intelligence has greatly facilitated translation processes, including machine translation of texts. Initially, it worked on the basis of rules and statistical models, i.e., translated text based on certain patterns and word frequencies. However, these methods were often inaccurate and had many limitations.
The real breakthrough came in the 21st century with the development of deep learning. Scientists began to use neural networks, a technology that mimics the way the human brain works. As a result, translations sounded more natural and accurate, as such systems better understood the context and meaning of words.
Today, neural machine translation is being actively improved thanks to new technologies in the field of artificial intelligence. NMT models learn to take into account language nuances and use special mechanisms that analyze even the smallest details of the text.
This helps translate even more accurately, cover more languages, and adapt to different topics and styles. For instance, when platforms like Hidden Casino aim to localize their content for international audiences, NMT systems can ensure that the tone, terminology, and cultural nuances are preserved across different languages. While this technology is not yet perfect, NMT is becoming more and more sophisticated over time, providing vital support for businesses and services in the digital space.
Among the most popular NMT services used by translators are ChatGPT, Socrat, Sider, Copilot, DeepL, Grammarly, Google Translate, and CAT tools such as Smartcat, memoQ, and Memsource.
Benefits of using AI for translation
Although automated services still can’t compare to human expertise, there are many situations where they become indispensable and extremely convenient.
Rapid processing of large amounts of text. Artificial intelligence significantly speeds up the overall process. Therefore, its use in large-scale projects with complex, specialized texts, such as technical documentation or financial reports, allows you to get quick results and meet deadlines.
Support for real-time communication. AI-powered automatic systems are an ideal solution for online meetings, webinars, or video conferences, as they allow participants to communicate effectively without experiencing a language barrier.
Application on a limited budget. Using AI for multilingual tasks is often cheaper than hiring a professional, especially for large projects. This is relevant for small and medium-sized businesses, as it can significantly reduce the cost of preparing multilingual content.
Scaling up and entering the international market. AI-powered services simplify the localization of content, websites, apps, and marketing materials, helping companies cover multiple markets simultaneously and effectively serve customers in different languages.
Integration with modern technologies. AI systems can be easily integrated into project management services, e-commerce platforms, or CRM systems. This allows you to automate some business processes, such as language support for customers or marketing campaigns, ensuring easy and convenient multilingual communication within the team.
Fast post-editing. Automated AI outputs can be the basis for post-editing by experienced linguists. This saves time and effort, as they only need to refine the content rather than create it from scratch.
As you can see, in many cases, using artificial intelligence not only saves time and money but also makes the process easier and more affordable. However, when it comes to accuracy, there is a trade-off.
Where AI translation still loses out to humans?
AI translation still has many pitfalls, and they all relate to quality.
Consistency of terminology and accuracy
In machine translation, it is very easy to misinterpret the source text, which leads to the use of incorrect vocabulary. This often happens with highly specialized terms, when the machine can substitute concepts or create many variants of the same word, disrupting the consistency of terms and thus changing the information that the translator is supposed to convey to the reader. The longer the document, the more likely it is that such inconsistencies will appear.
This won’t be a big problem for someone translating an email. However, it can be disastrous when translating legal text, technical or medical documents. In addition, the accuracy of AI translations varies from language to language – the more common it is, the higher the output quality.
Context, subject matter, and cultural sensitivities
Automated systems do a good job when it comes to literal rendering, but they are not as good at analyzing and taking into account context as humans. Even a minor mistake can result in a meaningless sentence or an entire paragraph. For example, Coors, the American beer company, tried to translate the slang phrase “turn it loose” into Spanish.
However, the brand faced an epic fail in the Spanish market, as the translated slogan unintentionally meant “suffer from diarrhea.” They attracted plenty of attention—for all the wrong reasons. In such a case, the only hope is post-editing, during which a qualified linguist checks and corrects all high-tech errors.
Another disadvantage of AI systems is cultural sensitivity: despite the wide capabilities of machines, they are still no substitute for experienced professionals with deep knowledge of local cultures, dialects, and customs. Unadapted, direct conversions can be misleading or even offensive to locals.
In addition, the machine is not yet able to convey humor and jokes accurately and precisely. Therefore, AI is not used as a sole performer in localization processes.
Responsibility and expertise
In difficult cases, such as when translating narrow industry-specific texts, a qualified translator will not guess at coffee grounds to find the equivalent of a term he or she does not know. They can always consult with more experienced colleagues and industry experts or get feedback directly from the author of the source text, website owner, or game developer.
A true professional is responsible for the quality of the translation with his or her reputation and fee, so he or she is interested in an accurate and appropriate result, unlike a soulless machine.
So what’s the bottom line?
So, the answer to the question ‘Will artificial intelligence really replace translators?’ is obvious: it’s still a long way off. An experienced linguist understands all the pitfalls of translation and knows how to adapt the source text into the target language without compromising the context and preserving the emotional coloring.
And such services as DeepL, Google Translate, Sider, Copilot, and others, despite using complex algorithms for fast translation, can be indispensable in situations where accuracy is not of paramount importance. In the case of professional post-editing, as machines still cannot replicate the cognitive processes of humans, experience emotions and understand subtexts.
Artificial intelligence has become a reliable assistant in translation processes, but it cannot yet be a full-fledged sole translator in complex projects. Instead, most services use machine learning capabilities to complement the work of humans, not replace them completely.
