Will Machine Learning AI Make Human Translators An Endangered Species? by Bernard Marr
Translating between human languages is something which artificial intelligence – specifically machine learning – has proven to be very competent at.
So much so that the CEO of one of the world’s largest employers of human translators has warned that many of them should be facing up to the stark reality of losing their job to a machine.
One Hour Translation CEO Ofer Shoshan told me that within one to three years, neural machine technology (NMT) translators will carry out more than 50% of the work handled by the $40 billion market.
His words stand in stark contrast to the often-repeated maxim that, in the near future at least, artificial intelligence will primarily augment, rather than replace, human professionals.
Shoshan told me that the quality of machine translation has improved by leaps and bounds in recent years, to the point where half a million human translators and 21,000 agencies could soon find themselves out of work.
He says, "The analogy that we can use is Kodak and digital photography - Kodak didn't see it coming …"
Quantifying this, Shoshan tells me that today on average 10% of a machine-translated document needs to be fine-tuned by humans to meet the standards expected by his company's Fortune 500 clients. Just two years ago, that figure was around 80%.
This has been made possible by the switch to neural machine translation – sometimes known as deep learning – adopted by the most advanced machine translation tools. Previously these relied on a method known as statistical translation. Google, Bing, and Amazon now all use NMT in their translation engines.