By Hagen Weiss
With the rapid advancement of machine learning capabilities, whether machines can replace human translation naturally arises. The benefits of automation, large databases, and lower costs make automatic translation attractive to many. Free software tools like Google Translate or DeepL Translate also make it easy for everyday users to translate text.
Despite the many obvious benefits of AI, there are drawbacks. Here are some reasons why machines can’t replace human translation (and likely won’t for some time).
Machine learning works primarily on rule-based logic. It relies on fixed rules based on datasets to decipher meaning. The game “chess” is a good example of where machine learning really shines. Chess is a rule-based game with defined parameters on how to play. These rules allow machines to be extremely effective when playing against even the world’s brightest human chess players.
Human language, on the other hand, is very different. Rules of communication can often be broken. Also, meaning can be implicit and not always clear.
Machines typically start by breaking down the structure of sentences to decipher meaning. Conversely, human translators start by gathering context to better understand the meaning. Context is key when it comes to translating ambiguous text.
Rarely do words have a direct one-to-one relationship. Words are infused with cultural nuances, preconceptions, and historical context. These nuances make it extremely difficult for machines to pick up on.
For instance, the English culture is very direct, factual, and forthcoming in addressing one another. However, in many cultures, this same attitude could come off rude. For example, the honor-culture of many Asian nations makes a big difference in how you’d address an elder versus a child. Only a human translator with this cultural sensitivity would understand how to translate these types of texts effectively.
Evolving Nature of Human Translation Language
The nature of language is never static. It is constantly evolving. Many words or phrases used today were not in use even 10-20 years ago. Moreover, new ideas, concepts, products, etc. are continuously being introduced. Human translators can adapt much quicker to the evolving nature of language than machines can.
Keeping software updated is a resource-intensive task. Machine translation needs to keep up with things like:
- Latest vocabulary
- Language conventions
- Grammar rules
- Technological development
- And more…
As you can imagine, this can be a huge task. On top of all this, there are approximately 7,000 languages in the world. The amount of time, money, and expertise required to develop machine translation software for all these languages is much too big of a task.
Still Requires the Human Translation Touch
All quality translations require a human touch. A human can catch things like style and tone that a machine may not be able to. Even the understanding of what type of document you are translating is a key contextual factor to consider while translating. For example, the tone of a technical document is very different from one of a personal article.
A human translator adds a humanizing touch that can’t be replicated by machines. Even if translated by a machine, it must still go through a human to ensure sentence structure, grammar, and cultural references are appropriate.
To Wrap Up
Machine translation is getting more advanced in the modern age. Translators can utilize machines to aid in their translations. However, there is still a long way to go before machines can fully replace human translation.
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