About two years ago, Claudia von Vacano, executive director of UC Berkeley’s social science D-Lab, had a chat with Brittan Heller, the then-director of technology and society for the Anti-Defamation League (ADL). The topic: “the harassment of Jewish journalists on Twitter.”
Heller wanted to kick the offending trolls off the platform, and Vacano, an expert in digital research, learning, and language acquisition, wanted to develop the tools to do it. Both understood that neither humans nor computers alone were sufficient to root out the offending language.
So, in their shared crusade against “hate” speech and its malign social impacts, a partnership of “love” was born.
Hate speech, the stinking albatross around the neck of social media, has become increasingly linked to violence, even atrocity. Perhaps the most egregious recent example: “Robert Bowers, the accused shooter in the October massacre at Pittsburgh’s Tree of Life Synagogue, was reportedly inflamed by (and shared his own) anti-Semitic tirades on Gab, a platform popular with the Alt-Right.”
Currently, Google, Facebook and Twitter employ thousands of people to identify and jettison hateful posts. But humans are slow and expensive, and many find the work emotionally taxing—traumatizing, even. Artificial Intelligence and machine learning are the obvious solution: “algorithms that can work effectively at both speed and scale.”
Unfortunately, hate speech is as “slippery as it is loathsome.” It doesn’t take a very smart “AI” to recognize an overtly racist or anti-Semitic epithet. But more often than not, today’s hate speech is deeply colloquial, or couched in metaphor or simile. The programs that have been developed to date simply aren’t up to the task.
That’s where Vacano and Heller come in. Under Vacano’s leadership, researchers at D-Lab are working in cooperation with the ADL on a “scalable detection” system—the Online Hate Index (OHI)—to identify hate speech. The tool learns as it goes, combining artificial intelligence, machine learning, natural language processing, and good old human brains to winnow through terabytes of online content. Eventually, developers anticipate major social media platforms will use it to recognize and eliminate hate speech rapidly and at scale, accommodating evolutions in both language and culture.
“The tools that were—and are—available are fairly imprecise and blunt,” says Vacano, “mainly involving keyword searches. They don’t reflect the dynamic shifts and changes of hate speech, the world knowledge essential to understanding it. Hate speech purveyors have become very savvy at getting past the current filters—deliberately misspelling words or phrases.” Current keyword algorithms, for example, can be flummoxed by something as simple as substituting a dollar sign ($) for an “S.”
Another strategy used by hate mongers is metaphor: “Shrinky Dinks,” for example, the plastic toys that shrink when baked in an oven, allude to the Jews immolated in the concentration camps of the Third Reich. Such subtle references are hard for current AI to detect, Vacano says.
The OHI intends to address these deficiencies. Already, their work has attracted the attention and financial support of the platforms that are most bedeviled—and that draw the most criticism—for hate-laced content: Twitter, Google, Facebook, and Reddit.
But no matter how well intentioned, any attempt to control speech raises Constitutional issues. And the First Amendment is clear on the matter, says Erwin Chemerinsky, the dean of Berkeley Law.
“First, the First Amendment applies only to the government, not to private entities,” Chemerinsky stated in an email to California. “Second, there is no legal definition of hate speech. Hate speech is protected by the First Amendment.” Unless it directly instigates violence, that is, an exception upheld in the 1942 Supreme Court decision, Chaplinksy v New Hampshire.
In other words, the platforms can decide what goes up on their sites, whether it’s hateful or not. Vacano acknowledges this reality: D-Lab, she says, isn’t trying to determine the legality, or even appropriateness, of moderating hate speech.
These “Artificial Intelligence” tools being developed by “Top Social Scientists Experts” in conjunction with the Anti-Capitalism Defamation League called the “Online Hate Index” will allow Twitter, Facebook, Google and others to prevent any “Hate Speech” from ever appearing on Social Media, thereby keeping the thoughts of the people pure.
These important “AI Tools” are already keeping people from hearing nary a discouraging word about Socialism. However, that exposes them to accusations of being haters themselves. How do they answer that?
Hate, hate me do
it’s hatred you spew
You’ve all come unglued
So ple-e-e-e-e-ase
Hate me do
Hate, hate me do
Your mask is askew
Your real self shines thru
So ple-e-e-e-e-ase
Hate me do
Someone who hates
Someone’s a shrew
Want us not great
Someone like you
Hate, hate me do
The smear’s your go-to
Your cred debts accrue
So ple-e-e-e-e-e-se
Hate me do
Hate, hate me do
Comeuppance is due
No blue wave for you
So ple-e-e-e-e-ase
Hate me do
Whoa, hate me do
Yeah, see you spew
Whoa, come unglued
Whoa, such a shrew
Yeah, hate me do
I guess it is okay to hate if you hate “hate speech” by haters who hate.
