Zuckerberg: US government inaction allowed fake news to spread

Facebook CEO Mark Zuckerberg speaks during the annual F8 summit at the San Jose McEnery Convention Center in San Jose, California. (AFP)
Updated 27 June 2019

Zuckerberg: US government inaction allowed fake news to spread

  • The CEO also called on governments to further regulate private data, political advertising and step up efforts to prevent state actors from interfering in US elections
  • Zuckerberg also said the leading social network is struggling to find ways to deal with “deepfake” videos

SAN FRANCISCO: Facebook boss Mark Zuckerberg said Wednesday that a lack of action by US authorities on fake political content on the platform after the 2016 US election helped pave the way for a subsequent avalanche of online disinformation.
The CEO — who has himself been widely criticized for a lackluster response to fake news — also called on governments to further regulate private data, political advertising and step up efforts to prevent state actors from interfering in US elections.
“As a private company we don’t have the tools to make the Russian government stop... our government is the one that has the tools to apply pressure to Russia,” he said during an on-stage interview at the Aspen Ideas Festival in Colorado.
“After 2016 when the government didn’t take any kind of counter action, the signal that was sent to the world was that ‘ok we’re open for business’, countries can try to do this stuff... fundamentally there isn’t going to be a major recourse from the American government.”
Zuckerberg also said the leading social network is struggling to find ways to deal with “deepfake” videos which have the potential to deceive and manipulate users on a massive scale.
The comments come amid growing concern over deepfakes — which are altered by using artificial intelligence to appear genuine — being used to manipulate elections or potentially spark unrest.
Earlier this month, Facebook’s Instagram network decided not to take down a fake video of Zuckerberg himself, saying the CEO would not get special treatment.
Online platforms have been walking a fine line, working to root out misinformation and manipulation efforts while keeping open to free speech.
Zuckerberg said this is a constant challenge, repeating his position that Facebook should not be an arbiter of truth on the Internet.
“I do not think we want to go so far toward saying that a private company prevents you from saying something that it thinks is factually incorrect to another person,” he said.


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.