'FB has no mechanism to detect hate content in regional languages'


New Delhi, Oct 7 (IANS): After whistleblower Frances Haugen accused Facebook of not taking action on fear-mongering and hate content related to India because of "the lack of Hindi and Bengali classifiers," experts said Facebook has no mechanism to deal with hate content in local or regional languages.

Arvind Gupta, social media expert and head of Digital India Foundation, told IANS, "Whether Facebook accepts it or not, it is a fact that it has no mechanism to deal with content in regional languages and that is why this kind of problem keeps arising."

Rejecting the bid to link this entire controversy with any political party, Gupta said that it has nothing to do with it. He said that pages using hate mongering are never official pages on Facebook. But it is a fact that Facebook has not yet taken any concrete steps to stop it, he added.

On the question of targeting Hindi and Bengali in particular, he said that such a problem can also be associated with many other languages as Facebook does not have people who understand the local languages.

In a statement to IANS, a Facebook spokesperson said that over the years, they have invested significantly in technology that proactively detects hate speech, "even before people report it to us".

"We now use this technology to proactively detect violating content in Hindi and Bengali, alongside over 40 languages globally," the spokesperson added.

"In addition, we have a team of content reviewers covering 20 Indian languages. As hate speech against marginalised groups, including Muslims, continues to be on the rise globally, we continue to make progress on enforcement and are committed to updating our policies as hate speech evolves online," the spokesperson added.

According to Haugen's complaint filed with the US Securities and Exchange Commission (SEC), "RSS Users, Groups, and Pages promote fear-mongering, anti-Muslim narratives targeted pro-Hindu populations with V&I (violence and inciting) intent".

An "Adversarial Harmful Networks - India Case Study", cited in one of the documents, quoted the author of the report as saying, "...and we have yet to put forth a nomination for designation of this group given political sensitivities".

The complaint by Haugen alleged that Facebook's internal records show there was a problem of "lack of Hindi and Bengali classifiers" to flag off such harmful content.

Classifiers are automated systems and algorithms that are designed to detect hate speech in content on the social media platform.

"There were a number of dehumanising posts (on) Muslims Our lack of Hindu and Bengali classifiers means much of this content is never flagged or actioned, and we have yet to put forth a nomination for designation of this group (RSS) given political sensitivities," the complaint read.

India is one of the biggest markets for the social network, with a user base of over 400 million for Facebook and WhatsApp each, according to third-party data.

Both the BJP and the RSS were yet to comment on the complaint.

In the past, Facebook has faced several allegations of inaction against hate content in India.

In January this year, a Parliament Standing Committee on Information Technology (I&T) had issued summons to officials of Facebook and Twitter to question them over misuse of the social media or online news platforms. The committee has also questioned Facebook's India head Ajit Mohan over the issue of political bias on the social media platform.

The allegations of a Facebook bias towards the BJP were reported in The Wall Street Journal in August 2020 and had claimed that Ankhi Das, the platform's then India Policy Head had opposed the idea of removing hate posts by BJP leaders, warning that this could hamper their "commercial interests".

Das later quit Facebook.

Meanwhile, Facebook CEO Mark Zuckerberg has posted a staunch defense of his company in a note to employees, saying that recent claims by an ex-employee about the social network's negative effects on society "don't make any sense".

 

  

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