Turkey tries Bloomberg reporters, accused of economic sabotage

Two Bloomberg reporters went on trial on Friday over claims they tried to sabotage the economy with an article about last year’s currency crisis. (AFP)
Updated 20 September 2019

Turkey tries Bloomberg reporters, accused of economic sabotage

  • They were among dozens of defendants, including some who had simply written jokes about the currency crisis on Twitter
  • Conspiracy theories are widely believed in Turkey

ISTANBUL: Two Bloomberg reporters on Friday appeared in a Turkish court accused of damaging the country’s economy by writing an article about last year’s currency crisis.

Numerous other defendants, including economists and journalists, have also been charged in the case over their critical comments on social media about the financial turmoil in August 2018.

If found guilty they could face up to five years in prison.

Bloomberg’s editor-in-chief, John Micklethwait, said: “We condemn the indictment issued against our reporters, who have reported fairly and accurately on newsworthy events. We fully stand by them and will support them throughout this ordeal.”

The case, which opened in Istanbul on Friday, was brought after a complaint from Turkey’s banking watchdog BDDK and Capital Markets Board. The criminal court will begin hearing the second session of the prosecution on Jan 17.

The Bloomberg reporters’ article angered Turkish decision-makers and financial institutions after it claimed that the country’s Central Bank would be holding an emergency meeting over a plunge in the value of the lira against the dollar — the biggest currency shock to hit Turkey since 2001 — mainly brought on by a diplomatic crisis with the US.

The independence of the Turkish Central Bank has been high on the agenda for some time in the recession-hit economy, especially after the dismissal of its governor by a presidential decree in early July with no official reason given.

Experts said the trial was a continuation of a campaign of intimidation against journalists working in independent local and foreign media in Turkey. One local journalist, Cengiz Erdinc, has been convicted of “ruining the prestige” of the state-run Ziraat bank.

Last year, the Turkish Interior Ministry said it would take legal action against 346 social media accounts it claimed had created negative perceptions about the Turkish economy.

In another attempted press crackdown in Turkey, the pro-government SETA think tank in Istanbul recently published a report profiling Turkish journalists working for foreign media organizations, including Arab News, accusing them of “carrying out a perception work” through their “univocal line of reporting.”

Dr. Sarphan Uzunoglu, assistant professor of multimedia journalism at the Lebanese American University, said Turkey’s existing foreign policy and the government’s discourse over the last two years, totally fitted what was going on in the Bloomberg trial.

“The (Turkish) Justice and Development Party’s paranoid and conspiracy-driven political discourse is directly reflected to accusations against these journalists,” he told Arab News.

“Journalists are accused of attempting an ‘economic coup.’ The tweets and stories they published, like in all trials of journalists in Turkey, are used against them. I think one of the most important factors here is that Bloomberg seems to be a handful of comparatively independent, economy focused newsrooms.”

On the day of the trial, the US dollar/Turkish lira exchange rate rose to 5.7140, from 5.6980 on Thursday. The Turkish economy has contracted for the past three quarters.


Facebook researchers use maths for better translations

Updated 15 min 19 sec ago

Facebook researchers use maths for better translations

  • Powerful automatic translation is a big priority for Internet giants

PARIS: Designers of machine translation tools still mostly rely on dictionaries to make a foreign language understandable. But now there is a new way: numbers.
Facebook researchers say rendering words into figures and exploiting mathematical similarities between languages is a promising avenue — even if a universal communicator a la Star Trek remains a distant dream.
Powerful automatic translation is a big priority for Internet giants. Allowing as many people as possible worldwide to communicate is not just an altruistic goal, but also good business.
Facebook, Google and Microsoft as well as Russia’s Yandex, China’s Baidu and others are constantly seeking to improve their translation tools.
Facebook has artificial intelligence experts on the job at one of its research labs in Paris.
Up to 200 languages are currently used on Facebook, said Antoine Bordes, European co-director of fundamental AI research for the social network.
Automatic translation is currently based on having large databases of identical texts in both languages to work from. But for many language pairs there just aren’t enough such parallel texts.
That’s why researchers have been looking for another method, like the system developed by Facebook which creates a mathematical representation for words.
Each word becomes a “vector” in a space of several hundred dimensions. Words that have close associations in the spoken language also find themselves close to each other in this vector space.
“For example, if you take the words ‘cat’ and ‘dog’, semantically, they are words that describe a similar thing, so they will be extremely close together physically” in the vector space, said Guillaume Lample, one of the system’s designers.
“If you take words like Madrid, London, Paris, which are European capital cities, it’s the same idea.”
These language maps can then be linked to one another using algorithms — at first roughly, but eventually becoming more refined, until entire phrases can be matched without too many errors.
Lample said results are already promising.
For the language pair of English-Romanian, Facebook’s current machine translation system is “equal or maybe a bit worse” than the word vector system, said Lample.
But for the rarer language pair of English-Urdu, where Facebook’s traditional system doesn’t have many bilingual texts to reference, the word vector system is already superior, he said.
But could the method allow translation from, say, Basque into the language of an Amazonian tribe?
In theory, yes, said Lample, but in practice a large body of written texts are needed to map the language, something lacking in Amazonian tribal languages.
“If you have just tens of thousands of phrases, it won’t work. You need several hundreds of thousands,” he said.
Experts at France’s CNRS national scientific center said the approach Lample has taken for Facebook could produce useful results, even if it doesn’t result in perfect translations.
Thierry Poibeau of CNRS’s Lattice laboratory, which also does research into machine translation, called the word vector approach “a conceptual revolution.”
He said “translating without parallel data” — dictionaries or versions of the same documents in both languages — “is something of the Holy Grail” of machine translation.
“But the question is what level of performance can be expected” from the word vector method, said Poibeau.
The method “can give an idea of the original text” but the capability for a good translation every time remains unproven.
Francois Yvon, a researcher at CNRS’s Computer Science Laboratory for Mechanics and Engineering Sciences, said “the linking of languages is much more difficult” when they are far removed from one another.
“The manner of denoting concepts in Chinese is completely different from French,” he added.
However even imperfect translations can be useful, said Yvon, and could prove sufficient to track hate speech, a major priority for Facebook.