Facebook has agreed to a $52 million court settlement to compensate content moderators who suffered mental trauma from the graphic and violent images they were required to review, plaintiff lawyers said Tuesday.

The agreement submitted to a California state court will include payments to more than 10,000 current and former content moderators who worked for firms contracted by Facebook.

The class-action lawsuit filed in 2018 claimed that the content reviewers were subject to psychological trauma from repeated exposure to graphic content such as child sexual abuse, beheadings, terrorism, animal cruelty, rape and murder.

All of the plaintiffs in the class action will get at least $1,000 and those diagnosed with specific mental health conditions such as post-traumatic stress disorder will get additional compensation up to $50,000.

Facebook also agreed to take measures to provide content moderators employed by its contractors in the United States with mental health support and counseling.

"We are so pleased that Facebook worked with us to create an unprecedented program to help people performing work that was unimaginable even a few years ago," plaintiff attorney Steve Williams of the Joseph Saveri Law Firm said in a statement.

"The harm that can be suffered from this work is real and severe. This settlement will provide meaningful relief, and I am so proud to have been part of it."

The case stemmed from news reports in The Guardian and The Verge highlighting the stress and difficult conditions of moderators hired by Facebook contractors.

According to the lawsuit, lead plaintiff Selena Scola told The Guardian: "You'd go into work at 9 am every morning, turn on your computer and watch someone have their head cut off. Every day, every minute, that's what you see. Heads being cut off."

Facebook trains AI on 'hateful memes'
Washington (AFP) May 12, 2020 - Facebook unveiled an initiative Tuesday to take on "hateful memes" by using artificial intelligence, backed by crowd sourcing, to identify maliciously motivated posts.

The leading social network said it had already created a database of 10,000 memes -- images often blended with text to deliver a specific message -- as part of a ramped-up effort against hate speech.

Facebook said it was releasing the database to researchers as part of a "hateful memes challenge" to develop improved algorithms to detect hate-driven visual messages, with a prize pool of $100,000.

"These efforts will spur the broader AI research community to test new methods, compare their work, and benchmark their results in order to accelerate work on detecting multimodal hate speech," Facebook said in a blog post.

Facebook's effort comes as it leans more heavily on AI to filter out objectionable content during the coronavirus pandemic that has sidelined most of its human moderators.

Its quarterly transparency report said Facebook removed some 9.6 million posts for violating "hate speech" policies in the first three months of this year, including 4.7 million pieces of content "connected to organized hate."

Facebook said AI has become better tuned at filtering as the social network turns more to machines as a result of the lockdowns.

Guy Rosen, Facebook vice president for integrity, said that with AI, "we are able to find more content and can now detect almost 90 percent of the content we remove before anyone reports it to us."

Facebook said it made a commitment to "disrupt" organized hateful conduct a year ago following the deadly mosque attacks in New Zealand which prompted a "call to action" by governments to curb the spread of online extremism.

Automated systems and artificial intelligence can be useful, Facebook said, for detecting extremist content in various languages and analyzing text embedded in images and videos to understand its full context.

Mike Schroepfer, Facebook's chief technology officer, told journalists on a conference call that one of the techniques helping this effort was a system to identify "near identical" images, to address the reposting of malicious images and videos with minor changes to evade detection.

"This technology can detect near perfect matches," Schroepfer said.

Heather Woods, a Kansas State University professor who studies memes and extremist content, welcomed Facebook's initiative and inclusion of outside researchers.

"Memes are notoriously complex, not only because they are multimodal, incorporating both image and text, as Facebook notes, but because they are contextual," Woods said.

"I imagine memes' nuance and contextual specificity will remain a challenge for Facebook and other platforms looking to weed out hate speech."

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