Access Business Analytics
Every day, nearly three quintillion bytes of digitized data come into being – a quintillion is one thousand trillions – so that means 3 × 1018 (“The Calculus of Global Content”). This daily wave of new content supports interactions and transactions across the entire spectrum of human and machine activity – and localizing it is essential for many international business, governmental, and humanitarian activities. There is no sign of this daily growth in content volume slowing down – and with it comes gigantic projects to transform and translate it for other purposes and markets.
How much of that daily flood of content gets professionally translated? We calculated the daily translation output of LSPs based on our Global Market Study sizing model, factored in some realistic assumptions about what actually would be worth translating, applied that to the daily tsunami of 3 × 1018 bytes, and determined that much less than 1% of that quotidian amount could possibly get translated by a human.
It would take 1,000 translators working full-time (that is, eight hours a day) for 61,375 work years to process 0.01% of the total volume into just one language. Reducing the total volume even further, we estimated it would still take two billion full-time translators to render all relevant content into the economically important languages. For some languages, the number of translators required would exceed the total pool of speakers.
How about using machine translation? The mainstream business press offers an increasingly confident – but fundamentally misguided – claim that today’s NMT is as good as, or has even surpassed, human translation. While machine translation could process vastly greater volumes, that increased availability from NMT comes at the cost of linguistic quality. Rather than write the obituary for human linguists, it’s time to confront the stark realities of this ever-growing pile of content. Few companies or governments are prepared to pay for − much less manage − all of the translation they’d like to do. And if they were ready to step up with the cash, maybe enrollment in foreign language studies and translations wouldn’t have dropped as dramatically as it has in recent years. The challenge for companies and governments is to apply the right translation modes to the right applications. Besides using ever-improving NMT software, it also means provisioning the few – and ever fewer – professionals who can translate with better tools so that they do it faster, better, and more efficiently. LSPs and in-house translation departments can pair CAT-equipped and MT-augmented humans with smarter software to:
In an environment where the popular business press and slick viral ads depicting cross-cultural romance promise that language is nothing more than a minor hurdle, investing in translator tools may seem like investing in rotary phones or cathode-ray-tube televisions. The fact of the matter is that human translation isn’t going anywhere for the foreseeable future, but translators and businesses need the capabilities offered by sophisticated but easy-to-use CAT tools. Far from being a waste, investment in them will deliver considerable advantages to users and help drive greater productivity.
Chief Research Officer
Focuses on market trends, business models, and business strategy
It Depends As your organization pivots toward integrating generative AI (GenAI) into more of its ...
In October 2023, we argued that the future of AI would be in “focused large language models” (FLLM...
The topic of automation has taken the interpreting industry by storm. On the one hand, enthusiasts b...
Back in the day when I first began working in localization, we didn’t have a translation management...
When friends and family hear what I’m working on these days, they typically ask: 1) won’t AI elimi...
Some people feel that using artificial intelligence (AI) to interpret human speech is a curse becaus...
Posts by CSA_Research