Reasons why machines can never replace human translators
As the machines become smarter and quicker, some human jobs are on the verge of becoming obsolete. However, it might not be the case with translation jobs. This article will give you five reasons why machines can never replace human translators.
There is an epic rise of international businesses, exchange of ideas, travel, and work division in the last decade. This has created a dire need for the people who can act as translators or interpreters for two or more parties.
On the other hand, with the development of technology, artificial intelligence (AI) has opened up ways that never seemed possible. Machine translation has become a way of life for many people. However, the question remains, “Whether machines can ever be smart enough to take over human translators?”
In our opinion, there are numerous reasons to believe that there is a long way to cover for computers before they can replace human translators. Here are some of the most prominent reasons:
1. Complexity of languages
Any language is a complex mix of words, phrases, idioms, dialects, cultural influences, and many more factors. A computer can only learn what we, the humans, program. It is nearly impossible for a machine to understand the subtle differences in the meaning of the words when any one of the above factors change.
There is one more factor affecting the complexity of the language and that is dialect. Accents and dialects differ as per the geography, age, occupation, ethnicity, etc. There are thousands of dialects of the English language alone spoken around the world. IDEA (International Dialects of English Archive) is an archive founded by Paul Meier, has 1600 samples from 120 countries of various English dialects and accents.
These complexities of languages make it almost impossible for its replication artificially. Hence, this is the leading factor in proving the fact that machines can never replace humans in translation.
2. Intonation and Inflexions
Humans speak in a voice that includes numerous intonations and inflections. The meaning of the dialogues will be completely different when these are removed from the language. The speech will become flat and lose its meaning.
Although machines are smart, they are still not intelligent enough to understand and perceive the language’s synthesis and its use.
3. Number of languages in the world
According to a Linguistic Society of America report, there were about 6909 distinct languages in 2009. If we look at the dialects and other versions of these languages, the list becomes endless. It will be nearly impossible to program all these languages in a computer to make a fully functional translator. The sheer amount of data will be a humongous task.
4. The Evolution of Language
The languages of the world are constantly evolving. Many languages absorb new words like a sponge. As more newer words are added, many words become obsolete and eventually deleted from the language. There are slangs which finally become the new normal. There are new situations that need new words, and those are “invented”.
Even the grammar of the languages evolves with time. Hence, a language is constantly new. It is almost impossible to make all those changes in a computer in real-time. The origins of the words in a language can only be known by a human translator. Many times, it is imperative in a speech how the word originated.
5. Context
The only way to understand the whole idea a person is trying to convey is by first understanding the context of the conversation. No sentence can stand on its own in a conversation. Computer translation does not take the context into account and thus can change the meaning of the conversation.
Final Words
Although artificial intelligence is making its mark on the world, humans are an indispensable part of the linguistic world. There will always be reasons why machines cannot replace human translators. Top-class translation agencies like The Translation Planet are doing a great job by giving their clients the benefits of human touch to the linguistic work.
