Is That a Fish in Your Ear?

Two side effects of the manner in which news is transmitted among different languages and communities of users are worth noting. The first is that it makes the “translatedness” of news completely invisible. However, even if the occlusion of translation is the express intention of the EU’s language-parity rule, it is not a fatality in the circulation of news and could easily be countered. A report of the latest speech by the Iranian president, for example, could perfectly well be attributed to a named journalist’s adaptation of a Reuters English-language wire originating in Kuwait based on a report in Arabic from Al Jazeera that had provided the information from listening to a radio broadcast in Farsi from Tehran. The second consequence of our collective unwillingness to track the language history of the things we are told by the media is to make us believe that the provision of international news is a straightforward matter, dependent only on the marvels of satellite telephones and data transmission. It is not. It is a burdensome business carried out by talented linguist-journalists working under tight constraints of time.

TWENTY-THREE The Adventure of Automated Language-Translation Machines

The reluctance of European peoples to retain Latin or to adopt some other transmission language—such as Esperanto—for the dissemination of important information has created a costly and difficult set of translation tasks, carried out under time pressures unimaginable in earlier ages. Now that nearly all other aspects of news transmission are carried out not by couriers but by electronic devices, it seems natural to ask why the core activity itself cannot be handled likewise, by automatic translation machines.

Although it is still in its infancy, machine translation has had an eventful and uneven history. It first arose in dramatic historical circumstances and in response to an overriding political need. It wasn’t initiated by an explicit act of political will, like the language rules of the European Union, but its launching ground was the climate of terror at the start of the Cold War. The United States had developed and used the atomic bomb. For the time being it had a monopoly on this terrible weapon. How long would the monopoly last? When would the Soviet Union catch up? One way of guessing the answer was to comb through all the research journals being published in the U.S.S.R., looking for clues as to the state of knowledge in the relevant disciplines.[145] The journals were in Russian. The United States needed either to train up a veritable army of Russian–English scientific translators—or to invent a machine that would do the job for them.

But it takes a long time to constitute a large group of translators from a language not widely known. There was no obvious source of English-educated, scientifically literate Russian translators in 1945, and so the authorities began to look toward machines. There were good reasons to think they could help with the urgent task of tracking the Soviets’ ability to design an atomic bomb.

The Second World War had fostered great advances in cryptography, the making and breaking of secret codes. Statistical techniques had been developed for decoding messages even when the language that had been encoded was not known. The astounding successes of the code breakers at the Bletchley Park site in England prompted some thinkers to wonder whether language itself could not be treated as a code. In a famous memorandum written in July 1949, Warren Weaver, then a senior official with the Rockefeller Foundation, found it “very tempting to say that a book written in Chinese is simply a book in English which was coded into the ‘Chinese code.’ If we have useful methods for solving almost any cryptographic problem, may it not be that with proper interpretation we already have useful methods for translation?”[146]

Weaver was aware of the pioneering work of Claude Shannon and others in the nascent disciplines of information theory and cybernetics and could see that if language could be treated as a code, then there would be huge development contracts available for mathematicians, logicians, and engineers working on the new and exciting number-crunching devices that had only just acquired their modern name of “computers.” But the temptation to see “language as code” comes from much deeper sources than just an intuition that it would create interesting jobs for very smart boys.