Last fall, Google Translate rolled out a new-and-improved translation engine that it claimed was, at times, “nearly indistinguishable” from human translation. Jost Zetzsche could only roll his eyes. The German native had been working as a professional translator for 20 years, and he’d heard time and time again that his industry would be threatened by advances in automation. Every time, he’d found, the hype was overblown—and Google Translate’s makeover was no exception. It certainly wasn’t the key to translation, he thought.
But it was remarkably good . Google had spent the better part of 2016 reworking its translation tool to be powered by —and in doing so, it had created something unnervingly powerful. Google Translate, once known for producing stilted but passable translations, had begun producing fluid, highly accurate prose. The kind of output that, to the untrained eye, was nearly indistinguishable from human translation. A 15,000-word New York Times story hailed it as “the great awakening.” The engine quickly began learning new tricks, figuring out how to translate language pairs it hadn’t encountered before: If it could do English to Japanese and English to Korean, it could figure out Korean to Japanese. At last month’s Pixel 2 launch, Google took its ambitious agenda a step further, introducing wireless headphones that it promised could translate 40 languages in real-time.
Translators are not worried
Since IBM debuted its pioneering machine translation system in 1954, the notion of a flawless machine translator has captured the imagination of programmers and the public alike. Science fiction writers have seized upon the idea, serving up utopian visions ranging from Star Trek’s Universal Translator to The Hitchhiker’s Guide to the Galaxy’s Babel Fish. Human-level translation—fluent prose that captures the meaning of the source text—is a holy grail of : one of the “-complete” challenges that, if conquered, would indicate that a machine had reached a human level of intelligence. The fanfare around Google’s advances in neural machine translation implied that the grail was within reach—and, along with it, the moment when human workers become obsolete.
But translators have long been on the frontlines of -induced job panic, and they aren’t worried. In fact, some are delighted. For those that have seized on the potential of tools, productivity has skyrocketed, along with demand for their work. […]