Hatebase catalogues the world’s hate speech in real time so you don’t have to – gpgmail


Policing hate speech is something nearly every online communication platform struggles with. Because to police it, you must detect it; and to detect it, you must understand it. Hatebase is a company that has made understanding hate speech its primary mission, and it provides that understanding as a service — an increasingly valuable one.

Essentially Hatebase analyzes language use on the web, structures and contextualizes the resulting data, and sells (or provides) the resulting database to companies and researchers that don’t have the expertise to do this themselves.

The Canadian company, a small but growing operation, emerged out of research at the Sentinel Project into predicting and preventing atrocities based on analyzing the language used in a conflict-ridden region.

“What Sentinel discovered was that hate speech tends to precede escalation of these conflicts,” explained Timothy Quinn, founder and CEO of Hatebase. “I partnered with them to build Hatebase as a pilot project — basically a lexicon of multilingual hate speech. What surprised us was that a lot of other NGOs [non-governmental organizations] started using our data for the same purpose. Then we started getting a lot of commercial entities using our data. So last year we decided to spin it out as a startup.”

You might be thinking, “what’s so hard about detecting a handful ethnic slurs and hateful phrases?” And sure, anyone can tell you (perhaps reluctantly) the most common slurs and offensive things to say — in their language… that they know of. There’s much more to hate speech than just a couple ugly words. It’s an entire genre of slang, and the slang of a single language would fill a dictionary. What about the slang of all languages?

A shifting lexicon

As Victor Hugo pointed out in Les Miserables, slang (or “argot” in French) is the most mutable part of any language. These words can be “solitary, barbarous, sometimes hideous words… Argot, being the idiom of corruption, is easily corrupted. Moreover, as it always seeks disguise so soon as it perceives it is understood, it transforms itself.”

Not only is slang and hate speech voluminous, but it is ever-shifting. So the task of cataloguing it is a continuous one.

Hatebase uses a combination of human and automated processes to scrape the public web for uses of hate-related terms. “We go out to a bunch of sources — the biggest, as you might imagine, is Twitter — and we pull it all in and turn it over to Hatebrain. It’s a natural language program that goes through the post and returns true, false, or unknown.”

True means it’s pretty sure it’s hate speech — as you can imagine, there are plenty of examples of this. False means no, of course. And unknown means it can’t be sure; perhaps it’s sarcasm, or academic chatter about a phrase, or someone using a word who belongs to the group and is attempting to reclaim it or rebuke others who use it. Those are the values that go out via the API, and users can choose to look up more information or context in the larger database, including location, frequency, level of offensiveness, and so on. With that kind of data you can understand global trends, correlate activity with other events, or simply keep abreast of the fast-moving world of ethnic slurs.

Hate speech being flagged all around the world — these were a handful detected today, along with the latitude and longitude of the IP they came from.

Quinn doesn’t pretend the process is magical or perfect, though. “There are very few 100 percents coming out of Hatebrain,” he explained. “It varies a little from the machine learning approach others use. ML is great when you have an unambiguous training set, but with human speech, and hate speech, which can be so nuanced, that’s when you get bias floating in. We just don’t have a massive corpus of hate speech, because no one can agree on what hate speech is.”

That’s part of the problem faced by companies like Google, Twitter, and Facebook — you can’t automate what can’t be automatically understood.

Fortunately Hatebrain also employs human intelligence, in the form of a corps of volunteers and partners who authenticate, adjudicate, and aggregate the more ambiguous data points.

“We have a bunch of NGOs that partner with us in linguistically diverse regions around the world, and we just launched our ‘citizen linguists’ program, which is a volunteer arm of our company, and they’re constantly updating and approving and cleaning up definitions,” Quinn said. “We place a high degree of authenticity on the data they provide us.”

That local perspective can be crucial for understanding the context of a word. He gave the example of a word in Nigeria, which when used between members of one group means friend, but when used by that group to refer to someone else means uneducated. It’s unlikely anyone but a Nigerian would be able to tell you that. Currently Hatebase covers 95 languages in 200 countries, and they’re adding to that all the time.

Furthermore there are “intensifiers,” words or phrases that are not offensive on their own but serve to indicate whether someone is emphasizing the slur or phrase. Other factors enter into it too, some of which a natural language engine may not be able to recognize because it has so little data concerning them. So in addition to keeping definitions up to date, the team is also constantly working on improving the parameters used to categorize speech Hatebrain encounters.

Building a better database for science and profit

The system just ingested its millionth hate speech sighting (out of perhaps tens times that many phrases evaluated), which sounds simultaneously like a lot and a little. It’s a little because the volume of speech on the internet is so vast that one rather expects even the tiny proportion of it constituting hate speech to add up to millions and millions.

But it’s a lot because no one else has put together a database of this size and quality. A vetted, million-data-point set of words and phrases classified as hate speech or not hate speech is a valuable commodity all on its own. That’s why Hatebase provides it for free to researchers and institutions using it for humanitarian or scientific purposes.

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But companies and larger organizations looking to outsource hate speech detection for moderation purposes pay a license fee, which keeps the lights on and allows the free tier to exist.

“We’ve got, I think, four of the world’s ten largest social networks pulling our data. We’ve got the UN pulling data, NGOs, the hyper local ones working in conflict areas. We’ve been pulling data for the LAPD for the last couple years. And we’re increasingly talking to government departments,” Quinn said.

They have a number of commercial clients, many of which are under NDA, Quinn noted, but the most recent to join up did so publicly, and that’s TikTok. As you can imagine, a popular platform like that has a great need for quick, accurate moderation.

In fact it’s something of a crisis, since there are laws coming into play that penalize companies enormous amounts if they don’t promptly remove offending content. That kind of threat really loosens the purse strings; If a fine could be in the tens of millions of dollars, paying a significant fraction of that for a service like Hatebase’s is a good investment.

“These big online ecosystems need to get this stuff off their platforms, and they need to automate a certain percentage of their content moderation,” Quinn said. “We don’t ever think we’ll be able to get rid of human moderation, that’s a ridiculous and unachievable goal; What we want to do is help automation that’s already in place. It’s increasingly unrealistic that every online community under the sun is going to build up their own massive database of multilingual hate speech, their own AI. The same way companies don’t have their own mail server any more, they use Gmail, or they don’t have server rooms, they use AWS — that’s our model, we call ourselves hate speech as a service. About half of us love that term, half don’t, but that really is our model.”

Hatebase’s commercial clients have made the company profitable from day one, but they’re “not rolling in cash by any means.”

“We were nonprofit until we spun out, and we’re not walking away from that, but we wanted to be self-funding,” Quinn said. Relying on the kindness of rich strangers is no way to stay in business, after all. The company is hiring and investing in its infrastructure, but Quinn indicated that they’re not looking to juice growth or anything — just make sure the jobs that need doing have someone to do them.

In the meantime it seems clear to Quinn and everyone else that this kind of information has real value, though it’s rarely simple.

“It’s a really, it’s a really complicated problem. We always grapple with it, you know, in terms of, well, what role does hate speech play? What role does misinformation play? What role do socioeconomics play?” he said. “There’s a great paper that came out of the University of Warwick, they studied the correlation between hate speech and violence against immigrants in Germany over, I want to say, 2015 to 2017. They graph it out. And its peak for peak, you know, valid for Valley. It’s amazing. We don’t do a hell of a lot of analysis — we’re a data provider.”

“But now have like, almost 300 universities pulling the data, and they do those kinds of those kinds of analyses. So that’s very validating for us.”

You can learn more about Hatebase, join the Citizen Linguists or research partnership, or see recent sightings and updates to the database at the company’s website.


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YouTube claims it removed 5x more hateful content in Q2, including 100K+ videos, 17K+ channels – gpgmail


In an update today, YouTube is claiming to have made significant progress in removing harmful video on its platform following a June update to its content policy which prohibited supremacist and other hateful content. The company says it has this quarter removed over 100,000 videos and terminated over 17,000 channels for hate speech — a 5x increase over Q1. It also removed nearly double the number of comments to over 500 million, in part due to an increase in hate speech removals.

The company, however, is haphazardly attempting to draw a line between what’s considered hateful content and what’s considered free speech.

This has resulted in what the U.S. Anti-Defamation League, in a recent report, referred to as a “significant number” of channels that disseminate anti-Semitic and white supremacist content being left online, following the June 2019 changes to the content policy.

YouTube CEO Susan Wojcicki soon thereafter took to the YouTube Creator blog to defend the company’s position on the matter, arguing for the value that comes from having an open platform.

“A commitment to openness is not easy. It sometimes means leaving up content that is outside the mainstream, controversial or even offensive,” she wrote. “But I believe that hearing a broad range of perspectives ultimately makes us a stronger and more informed society, even if we disagree with some of those views.”

Among the videos the ADL had listed were those that featured anti-Semitic content, anti-LGBTQ messages, those denied the Holocaust, featured white supremacist content, and more. Five of the channels it cited had, combined, over 81 million views.

YouTube still seems to be unsure of where it stands on this sort of content. While arguably these videos would be considered hate speech, much seems to be left online. YouTube also flip-flopped last week when it removed then quickly reinstated the channels of two Europe-based, far-right YouTube creators who espouse white nationalist views.

Beyond the hate speech removals, YouTube also spoke today of the methodology it uses to flag content for review.

It will often use hashes (digital fingerprints) to automatically catch copies of known prohibited content ahead of it being made public. This is a common way platforms remove child sexual abuse images and terrorist recruitment videos. However, this is not a new practice and its mention in today’s report could be to deflect attention from the hateful content and issues around that.

In 2017, YouTube said also increased its use of machine learning to help it find similar content to those that have already been removed, even before the videos are viewed. This is effective for fighting spam and adult content, YouTube says. In some cases, this can also help to flag hate speech, but machines don’t understand context so human review is still required to make the nuanced decisions.

Fighting spam is fairly routine these days, as it accounts for the majority of the removals — in Q2, nearly 67% of the videos removed were spam or scams.

Over 87% of the 9 million totals videos removed in Q2 were removed by automated systems, YouTube said. An upgrade to spam detection systems in the quarter led to a more than 50% increase in channels shut down for spam violations, it also noted.

The company said that more than 80% of the auto-flagged videos were removed without a single view in Q2. And it confirmed that across all of Google, there are over 10,000 people tasked with detecting, reviewing, and removing content that violates its guidelines.

Again, this over 80% figure largely speaks to YouTube’s success in using automated systems to remove spam and porn.

Going forward, the company says it will soon release a further update to its harassment policy, first announced in April, that will aims to prevent creator-on-creator harassment — as seen recently with the headline-grabbing YouTube creator feuds and the rise of “tea” channels.

YouTube additionally shared a timeline of its content policy milestones and related product launches.

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The update from YouTube comes at a critical time for the company, just ahead of a reported $200 million settlement with the FTC over alleged violations of child privacy laws. The fine serves as a stark reminder that, for years now, the viewers of these hate speech-filled videos haven’t only been adults interested in researching extremist content or engaging in debate, but also millions of children who today turn to YouTube for information about their world.


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Cloudflare will stop service to 8chan, which CEO Matthew Prince describes as a “cesspool of hate” – gpgmail


Website infrastructure and security services provider Cloudflare will stop providing service to 8chan, wrote Matthew Prince in a blog post, describing the site as a “cesspool of hate.” Service will be terminated as of midnight Pacific Time.

“The rationale is simple: they have proven themselves to be lawless and that lawlessness has caused multiple tragic deaths,” wrote Prince. “Even if 8chan may not have violated the letter of the law in refusing to moderate their hate-filled community, they have created an environment that revels in violating its spirit.”

The decision was made after the suspect in this weekend’s mass shooting at El Paso posted a lengthy racist and anti-immigration “manifesto” to 8chan almost immediately before the attack, which killed at least 20 people. Federal authorities are treating the shooting as an act of domestic terrorism and the Justice Department is also considering bringing federal hate crime and firearm charges, which both potentially carry the death penalty, against the shooter.

8chan was also used by the perpetrator in March’s terrorist attacks on two Christchurch, New Zealand mosques, as well as the suspect in the April shooting at a synagogue in Poway, California.

“The El Paso shooter specifically referenced the Christchurch incident and appears to have been inspired by the largely unmoderated discussions on 8chan which glorified the previous massacre,” wrote Prince. “In a separate tragedy, the suspected killer in the Poway, California synagogue shooting also posted a hate-filled ‘open letter’ on 8chan. 8chan has repeatedly proven itself to be a cesspool of hate.”

Before Cloudflare announced its decision to terminate service to 8chan, Prince spoke to reporters from the Guardian and the New York Times, telling the Guardian that he wanted to “kick 8chan off our network,” but also (in the later interview with the New York Times), expressing hesitation because terminating service may make it harder for law enforcement officials to access information on the site.

In his blog post, Prince explained Cloudflare’s ultimate decision to cut service, writing that more than 19 million Internet properties use Cloudflare’s services and the company “[did] not take this decision lightly.”

“We reluctantly tolerate content that we find reprehensible, but we draw the line at platforms that have demonstrated they directly inspire tragic events and are lawless by design. 8chan has crossed that line,” he wrote.” It will therefore no longer be allowed to use our services.”

This is not the first time Cloudflare has cut off service to a site for enabling the spread of racism and violence. Cloudflare previously terminated service to white supremacist site Daily Stormer in August 2017, but noted that the site went back online after switching to a Cloudflare competitor. “Today, the Daily Stormer is still available and still disgusting. They have bragged that they have more readers than ever. They are no longer Cloudflare’s problem, but they remain the Internet’s problem,” Prince wrote.

Prince says he sees the situation with 8chan playing out in a similar way. Since terminating service to the Daily Stormer, Prince says Cloudflare has worked with law enforcement and civil society organizations, resulting in the company “cooperating around monitoring potential hate sites on our network and notifying law enforcement when there was content that contained a legal process to share information when we can hopefully prevent horrific acts of violence.”

But Prince added that the company “continue[s] to feel incredibly uncomfortable about playing the role of content arbiter and do not plan to exercise it often,” adding that this is not “due to some conception of the United States’ First Amendment,” since Cloudflare is a private company (and most of its customers, and more than half of its revenue, are outside the United States).

Instead, Cloudflare “will continue to engage with lawmakers around the world as they set the boundaries of what is acceptable in those countries through due process of law. And we will comply with those boundaries when and where they are set.”

Cloudflare’s decision may increase scrutiny on Amazon, since the 8chan’s operator Jim Watkins sells audiobooks on Amazon.com and Audible, creating what the Daily Beast refers to as “his financial lifeline to the outside world.”




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