Translators often get asked about the impact of technology on their jobs. Between advancements in AI translation and the potential of big data, the industry has certainly seen shifts. So, what is the future of AI in the language translation industry?
Big data explained
Big data refers to very large amounts of data that can be analyzed to identify patterns and trends, and gain insights. When we talk about big data, we mean really big data, so large that it can be challenging to find ways to store and process it effectively.
Where does this data come from? Our actions, decisions, and digital habits leave traces that can be turned into data. From this, for example, a business might be able to analyze customer behavior on a large scale to predict what customers will do in the future.
Big data can be useful in the translation industry, from consumer insights to developing the latest tools in AI translation technology. For instance, with enough data from parallel texts in specific languages, AI machines can analyze structures, grammar, vocabulary, and more to create rapid translations.
What will AI translation look like in the future?
AI translation is continually being researched and developed, with new advancements adding possibilities for language service providers. Facebook recently reported that they have been developing an AI translation model that doesn’t center around English.
The company explains that if, for example, a translation is needed from Chinese to French, English-centric models would train from Chinese to English and English to French because English training data is the most widely available. They claim that training directly from Chinese to French preserves meaning far better.
Another example of advances in language translation technology can be found in the way programs handle texts. In recent years, translation tools have begun to consider full sentences rather than just individual words, meaning more of the linguistic context is taken into account.
Will AI replace human translators?
Advances like these spark the question “will AI replace human translators?”. Well, while AI translation can give individuals an insight into foreign-language texts, it just can’t be relied on for the high levels of accuracy needed in professional work. One mistake in a legal document, medical report, or even a marketing campaign could have a big impact.
An article from 2018 groups together the opinions of several academics in the field, explaining where AI translation is still lacking. Firstly, one of the drawbacks of AI translation is that machine learning works best with concrete scenarios and fixed rules. Language doesn’t always work this way; it can be subjective and dynamic. For example, irony and sarcasm aren’t always overt and the way we voice them can be culturally specific. How well can a computer deal with this?
What’s more, focusing purely on grammar and in-text information doesn’t give enough context for full language analysis. Dr. Jorge Majfud, Associate Professor of Spanish, Latin American Literature, and International Studies at Jacksonville University explains further:
“The problem is that considering the ‘entire’ sentence is still not enough. The same way the meaning of a word depends on the rest of the sentence…the meaning of a sentence depends on the rest of the paragraph and the rest of the text, as the meaning of a text depends on a larger context called culture, speaker intentions, etc.”
Working with AI translation tools
It doesn’t have to be all or nothing, however. Thanks to advancements in technology, human translators can use tools, including AI translation, as they see fit to work as efficiently as possible.
Most language service providers offer a range of solutions that can be tailored to each project and used in combination with human translation, including computer-assisted translation, MTPE, and neural machine translation networks (modeled on the human brain).
Here at Future Trans, we have over 25 years’ experience in the translation industry. We specialize in translating into Middle Eastern and African languages across a range of industries.