Privacy watchdogs warn Facebook over Libra currency

Facebook announced the launch of Libra in June. (File/AFP)
Updated 06 August 2019

Privacy watchdogs warn Facebook over Libra currency

  • Facebook was called to respond to more than a dozen concerns over how it will handle sensitive personal information of users of the digital currency
  • The letter follows a chorus of warnings about Facebook’s entry into the shadowy world of digital banking

SYDNEY: Global privacy regulators joined forces Tuesday to demand guarantees from Facebook on how it will protect users’ financial data when it launches its planned cryptocurrency, Libra.
The watchdogs from Australia, the US, EU, Britain, Canada and other countries issued an open letter calling on Facebook to respond to more than a dozen concerns over how it will handle sensitive personal information of users of the digital currency.
The letter follows a chorus of warnings about Facebook’s entry into the shadowy world of digital banking, including at a meeting last month of finance ministers and central bankers from the G7 group of most developed economies.
The watchdogs said that Facebook and its subsidiary Calibra “have failed to specifically address the information handling practices that will be in place to secure and protect personal information.”
Facebook’s handling of user data, highlighted by the Cambridge Analytica scandal, had “not met the expectations of regulators or their own users,” they said.
The social media giant’s latest project faced similar risks, they said, adding that the “combination of vast reserves of personal information with financial information and cryptocurrency amplifies our privacy concerns about the Libra Network’s design and data sharing arrangements.”
The regulators demanded Facebook provide guarantees that user information, such as transaction histories, will not be shared without explicit consent and that all personal data will be adequately secured by all parties in the Libra network.
Facebook announced the launch of Libra in June, with Calibra slated to run a digital wallet and provide financial services using blockchain technology.
The currency is to be overseen by a Geneva-based Libra Association of companies, and Swiss authorities have also pledged tight oversight of the operation.
Libra is widely regarded as a challenger to dominant global player bitcoin.
Expected to launch in the first half of 2020, Libra is designed to be backed by a basket of currency assets to avoid the wild swings of bitcoin and other cryptocurrencies.


Facebook researchers use maths for better translations

Updated 13 October 2019

Facebook researchers use maths for better translations

  • Facebook researchers say rendering words into figures and exploiting mathematical similarities between languages is a promising avenue
  • Allowing as many people as possible worldwide to communicate is not just an altruistic goal, but also good business

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.