Will Machine Translation Replace Human Translation?

Machine learning is described as the development of computer systems that are able to learn and adapt without any instructions. These computer systems use algorithms and other statistical models to help analyze patterns in data. The pattern analyzation is what allows the computer system to display a response. But in layman’s terms this is simply a robot that can respond to human interaction, and scary as it may be, we are working on robots responding to human emotion and displaying empathy as well.

One thing that machine learning can do is machine translation. You see this translation software used in our phones and on the internet. A good example is Google Translate.

Being in the translation industry can make you wonder if these robots can take over our job. Fortunately, machine translation robots will never live up to what humans can do with translation.

Robot Learning Limitations

When it comes to robots, they all have one thing in common – a human built them. This means that the robots can only do what they were programmed to do. They are given specific rules to operate by and don’t have the capacity to think for themselves. At least not yet. To keep it simple, these robots are only able to do what they are taught to do by repeating what humans have already done. ThereforeTherefore, it is limiting because robots are unable to think for themselves.

Progression of Technology In The Media

The way the media and tech companies talk about the progression of artificial intelligence, machine learning, and machine translation is scary, but not totally correct. They amp it making it seem as though this technology can replace humans with its power, but in fact it’s true purpose is to aid humans.

This type of technology helps humans be more efficient and decrease the amount of time it takes to do something. For example, a machine translator can help get a project started for a human translator who only then needs to edit the copy to ensure clarity.  But even here, the result is not a perfect result, nor is the output product usable for the majority of important translations. It’s a good ‘gist’ of things though.