It was hard to miss. Tencent, one of the biggest technology companies in China, aimed to show off their technological prowess by turning over the interpreting at their major tech showcase to a machine. And the results were … not great. The machine spouted gibberish, journalists were amused and suddenly the job of human interpreters seemed safe.
The problem is that most of the discussions of the whole affair were very short-sighted. For businesses and interpreters alike, such short-term “will humans have a job next year?” thinking is strategically useless. In fact, the whole “humans or AI” debate is misleading.
In this post, I will look at what business leaders, events professionals and other buyers need to learn from the Tencent fiasco. Next week, I will look at the perspective of interpreters.
So what do buyers need to learn from the Tencent machine interpreting fiasco?
Let’s start with the obvious: machine interpreting is not ready to be used at important events.
Despite the claims of companies selling the latest gadget and the claims of machine translation suppliers, the best that current technology can do is help you get directions to the train station or help you order pasta. In fact, the latter is even one of the use cases suggested by Google themselves!
There are many reasons why machine interpreting is not even nearly ready to take over your next event but the most important to remember at the moment is that machine interpreting can only deal with words. While words are important, they will always get their meaning from context, intonation and allusion.
Saying “we have no reservations” takes on entirely different meanings depending on who says it. If a hotel receptionist says it, it probably means that your travel agent has messed up. If a potential client says it five minutes before they are due to sign a large contract, it means something completely different. Currently, machine interpreting has no way of determining the wider context of how language is used, apart from sometimes being able to take into account what was said before.
Human interpreters are trained to understand language in context. This is why they ask for detailed briefs before they accept assignments. This is why sometimes they will refer assignments to their colleagues, who might know a specific context better than they do.
Until machine interpreting can understand the social and cultural context of what is being said, it will be as likely to get you in trouble and help you seal the deal.
The Tencent fiasco not only shows this principle in action but demonstrates the need to be highly critical of the claims of machine interpreting providers. Tencent’s claim of “97% accuracy” most likely came from laboratory results and limited in-house testing. The only results that matter from machine interpreting providers are the experience of clients using it in similar environments to you. For now, it will pay to ignore any research that comes out of testing laboratories. They simply don’t reflect real-life conditions.
This doesn’t mean that we should ignore or ridicule machine interpreting. It will have its uses. It may be worth equipping your sales team with it, to make it easier for them to find their way around foreign cities. One day soon, it may even make human interpreting more effective by helping interpreters to prepare better.
But its uses are still limited and there are still privacy concerns attached. Anything said into a machine interpreting app can and will be used as training data. As soon as you turn on machine interpreting, you basically sign away your rights to keep what you said private.
As much as the Tencent fiasco serves as a warning of the dangers in being overconfident in your newest product, it can and should launch some serious debates about the relevance and usefulness of such technologies for businesses and the extent to which we are happy to sign away privacy in return for technological improvements.
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