Facebook’s flawed approach to censorship reveals a challenge faced by AI. According to leaked documents, human censors at the social network have devised well-intentioned guidelines for removing posts containing hate speech or other offensive content. In practice, however, they create a confusing, often contradictory set of practices.
As ProPublica reported, a post from U.S. Representative Clay Higgins in which he called for the slaughter of radicalized Muslims was permissible. “Hunt them, identify them, and kill them,” he wrote. “Kill them all. For the sake of all that is good and righteous. Kill them all.” Meanwhile, a post by Didi Delgado, a Black Lives Matter activist, was removed: “All white people are racist. Start from this reference point, or you’ve already failed.”
As these two examples reveal, striking a balance between free speech and hate speech from a universal set of guidelines is fraught with peril. Applying such a framework for one country’s audience is difficult, and attempting to do so for a global audience — Facebook has two billion users, is even more difficult. What is acceptable to one group, will offend another.
It doesn’t matter if it’s humans or an AI that perform the censorship.
Irwin Gotlieb, chairman of GroupM, raised this topic in a conversation with Stephen Wolfram, founder of Wolfram Research, and me this spring. Gotlieb described the scenario of one AI-car carrying one passenger and another carrying several passengers; if only one vehicle could be saved, how would an AI system determine a response?
“At the moment there isn’t one solution for the world, and different parties will put different rule sets against it, with different objectives,” Gotlieb said.
“This question of ‘Can we invent one perfect set of mathematical principles that will determine the AIs for all eternity?’ — the answer, I think, is no,” Wolfram replied.
While our conversation was about car safety, the same challenges can be found in Facebook’s approach to censorship. As Abraham Lincoln famously said, “You can never please all of the people all the time.”
Facebook may be doing a lousy job, but it’s a nearly impossible task.
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Blaise Zerega
Editor in Chief
P.S. Please enjoy this video, “AI and Machine Learning – Technology Frontiers,” from MIT’s Initiative on the Digital Economy.
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