How human translators are coping with competition from powerful AI
Deep Dives
Explore related topics with these Wikipedia articles, rewritten for enjoyable reading:
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Transformer (deep learning)
15 min read
The article explicitly mentions that ChatGPT is based on the transformer architecture, first used by Google for machine translation in 2017. Understanding how transformers work provides essential context for why AI translation has improved so dramatically.
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Language localisation
12 min read
Video game localization is a central example in the article, with Marc Eybert-Guillon's work discussed extensively. This Wikipedia article explains the broader practice of adapting products for different markets, including the cultural and linguistic nuances that AI struggles with.
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Machine translation
15 min read
The entire article centers on how machine translation has affected human translators over the past decade. This Wikipedia article provides the historical and technical context for understanding the evolution from rule-based to neural machine translation systems.
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When ChatGPT was released last fall, a lot of white-collar workers had a chilling thought: “could this technology do my job?” A May survey by CNBC and SurveyMonkey found that almost a quarter of workers fear losing their jobs to AI in the next few years, including 51 percent of workers in advertising and marketing and 46 percent of those in business support and logistics.
But for one white-collar profession—translators—this stopped being a theoretical question years ago. ChatGPT is based on a neural network architecture called the transformer that was first used by Google for machine translation in 2017. So competition from AI has been an everyday reality for human translators for more than five years.
Marc Eybert-Guillon started his career as a translator in 2017. In 2020, he founded From the Void, a firm that helps video game makers localize their games for foreign markets.
“It's that meme of the guy with the noose around his neck,” Eybert-Guillon told me. The condemned man looks over at the guy standing next to him on the gallows and asks “first time?”
“We’ve been ‘in danger’ of being taken over by AI for 10 years now and it still hasn’t happened,” Eybert-Guillon said. “But we keep getting told that it’s going to happen.”
There are two big reasons AI hasn’t put many human translators out of work. First, human translators still do a better job in specialized fields like law and medicine. Translation errors in these fields can be very expensive, so clients are willing to pay extra for a human-quality translation.
Second, there has been rapid growth in hybrid translation services where a computer produces a first draft and a human translator checks it for errors. These hybrid services tend to be about 40 percent cheaper than a conventional human translation, and customers have taken advantage of that discount to translate more documents. Translators get paid
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