No wonder, half of it was at TIME magazine this morning:
A few hours from now.
From the Daily Beast, March 24:
If Trump Calls Kim Jong Un A ‘Fat Toad,’ His Interpreter Will Have to Translate It
There will be at least two other people in the room for this historic summit. And the weight of the world is on their every word.Related:
When Donald Trump meets with Kim Jong Un sometime
in the next two months, there is a non-zero chance that the high-stakes nuclear summit descends into rounds of school-yard taunting.
Should Trump call Kim “fat” and should Kim respond by calling Trump a “dotard”—as each, remarkably, has done in the past—it will fall on their respective interpreters to deliver those broadsides in the other’s dialect. And though doing so might precipitate a nuclear holocaust, there is nothing that can be done about it. The words will be translated.
“Yes, of course,” said Dimitry Zarechnak, who served as Ronald Reagan’s interpreter during his summit with former Soviet leader Mikhail Gorbachev, when asked if Trump’s interpreter would have to tell Kim that the president called him “little Rocket man.”
The discussions surrounding a potential Trump-Kim summit is already fairly volatile.
The president agreed to the meeting on a whim. But as recently as this past Thursday, he signalled his displeasure at having to go through with it at all. “This should have been done by somebody before they were in the position that they’re in right now,” he said at a White House event.
It’s not entirely clear if Trump will, in fact, go through with it. His former top adviser, Steve Bannon, has expressed his belief that it will be logistically impossible to pull off. And the appointment of former UN Ambassador John Bolton—a man who seems more disposed to preemptively bombing North Korea then talking with its leaders—as the new national security adviser makes the likelihood of a summit even more remote.
But should it transpire, one of the more critical responsibilities will fall on the interpreters. The role that they play in presidential tete-a-tetes is often overlooked, if not entirely ignored. And for good reason. The interpreter is, at his or her most basic level, a oratorical tool for a conversation between other individuals. They are accessories, not players.
But they don’t just robotically translate words either (indeed, they scoff at being called “translators” as opposed to “interpreters”). Often, indeed, their job involves a fair amount of intuition, study, and diplomacy. Those tasks become exceptionally more difficult at a summit with world leaders. For the one set to happen between Trump and Kim, the hurdles are even higher, do to the enigmatic nature of both leaders and the existential nature of the talk....MORE
Don't Swear at Nuns and Other Stories of Translation, Human and Machine
Shitloads and zingers: on the perils of machine translation
Years ago, on a flight from Amsterdam to Boston, two American nuns seated to my right listened to a voluble young Dutchman who was out to discover the United States. He asked the nuns where they were from. Alas, Framingham, Massachusetts was not on his itinerary, but, he noted, he had ‘shitloads of time and would be visiting shitloads of other places’.
The jovial young Dutchman had apparently gathered that ‘shitloads’ was a colourful synonym for the bland ‘lots’. He had mastered the syntax of English and a rather extensive vocabulary but lacked experience of the appropriateness of words to social contexts.Also related:
This memory sprang to mind with the recent news that the Google Translate engine would move from a phrase-based system to a neural network. (The technical differences are described here.) Both methods rely on training the machine with a ‘corpus’ consisting of sentence pairs: an original and a translation. The computer then generates rules for inferring, based on the sequence of words in the original text, the most likely sequence of words from the target language.
The procedure is an exercise in pattern matching. Similar pattern-matching algorithms are used to interpret the syllables you utter when you ask your smartphone to ‘navigate to Brookline’ or when a photo app tags your friend’s face. The machine doesn’t ‘understand’ faces or destinations; it reduces them to vectors of numbers, and processes them.
I am a professional translator, having translated some 125 books from the French. One might therefore expect me to bristle at Google’s claim that its new translation engine is almost as good as a human translator, scoring 5.0 on a scale of 0 to 6, whereas humans average 5.1. But I’m also a PhD in mathematics who has developed software that ‘reads’ European newspapers in four languages and categorises the results by topic. So, rather than be defensive about the possibility of being replaced by a machine translator, I am aware of the remarkable feats of which machines are capable, and full of admiration for the technical complexity and virtuosity of Google’s work.
My admiration does not blind me to the shortcomings of machine translation, however. Think of the young Dutch traveller who knew ‘shitloads’ of English. The young man’s fluency demonstrated that his ‘wetware’ – a living neural network, if you will – had been trained well enough to intuit the subtle rules (and exceptions) that make language natural. Computer languages, on the other hand, have context-free grammars. The young Dutchman, however, lacked the social experience with English to grasp the subtler rules that shape the native speaker’s diction, tone and structure. The native speaker might also choose to break those rules to achieve certain effects. If I were to say ‘shitloads of places’ rather than ‘lots of places’ to a pair of nuns, I would mean something by it. The Dutchman blundered into inadvertent comedy....
Why would Kim Jong-un insult me by calling me "old," when I would NEVER call him "short and fat?" Oh well, I try so hard to be his friend - and maybe someday that will happen!— Donald J. Trump (@realDonaldTrump) November 12, 2017