Facebook today published its annual transparency report, and for the first time included the number of items removed in each category that violated its content standards. While the company seems to be very proficient at removing nudity and terrorist propaganda, its lagging behind when it comes to hate speech. Of the six categories mentioned in the report, the number of hate speech posts Facebooks algorithms caught before users reported them was the lowest: For hate speech, our technology still doesnt work that well and so it needs to be checked by our review teams. We removed 2.5 million pieces of hate speech in Q1 2018 — 38 percent of which was flagged by our technology. Are you doing business in Amsterdam in May? Compare that percentage with the number of posts proactively purged for violent content (86 percent), nudity and sexual content (96 percent), and spam (nearly 100 percent). But thats not to say the relatively low number is due to an defect from Facebook. The problem with trying to proactively scour Facebook for hate speech is that the companys AI can only understand so much at the moment. How do you get an AI to understand the nuances of offensive and derogatory language when many humans struggle with the concept? Guy Rosen, Facebooks Vice President of Product Management, pointed out the difficulties of determining context: Its partly that technology like artificial intelligence, while promising, is still years away from being effective for most bad content because context is so important. For example, artificial intelligence isnt good enough yet to determine whether someone is pushing hate or describing something that happened to them so they can raise awareness of the issue. If a Facebook user makes a post speaking about their experience being called a slur in public, using the word in order to make a greater impact, does their post constitute hate speech? Even we were all to agree that it doesnt, how does one get an AI to understand the nuance? And what about words which are offensive in some language, but not another? Or homographs? Or, or, or — the caveats go on and on. When its being asked to read that kind of subtlety, it shouldnt be a surprise Facebooks AI has only thus far had a success rate of 38 percent. Facebook is attempting to keep false positives to a minimum by having each case reviewed by moderators. The company addressed the issue during its F8 conference: Understanding the context of speech often requires human eyes – is something hateful, or is it being shared to condemn hate speech or raise awareness about it? … Our teams then review the content so whats OK stays up, for example someone describing hate they encountered to raise awareness of the problem. Mark Zuckerberg waxed poetic during his Congressional testimony about Facebooks plans to use AI to wipe hate speech off its platform: I am optimistic that over a five-to-10-year period we will have AI tools that can get into some of the linguistic nuances of different types of content to be more accurate. With that estimate, itd be absurd to expect the technology to be as accurate as Zuckerberg hopes itd be now. Well have to check Facebooks transparency report in the next couple of years to see how the companys progressing. The Next Webs 2018 conference is almost here, and itll be . Find out all about our tracks here.
Facebook took enforcement action on 1.9 million posts related to terrorism by Al Qaeda and ISIS in the first quarter of this year, the company said, up from 1.1 million posts in the last quarter of 2018. The increased enforcement, which typically results in posts being removed and accounts being suspended or banned from Facebook, resulted from improvements in machine learning that allowed the company to find more terrorism-related photos, whether they were newly uploaded or had been on Facebook for longer. Facebook found 99.5 percent of terrorism-related posts before they were flagged by users, it said. In the previous quarter, 97 percent of posts were found by the company on its own. Facebook made the data available as part of its first ever Community Standards Enforcement Report, which documents content moderation actions taken by the company between October and March. Other findings in the report include: Graphic violence. Posts that included graphic violence represented from 0.22 percent to 0.27 percent of views, up from 0.16 to 0.19 percent in the previous quarter. The company took action on 3.4 million posts, up from 1.2 million in the previous quarter. It said violent posts appeared to have risen in conjunction with the intensifying conflict in Syria. Nudity and sex. Posts with nudity or sexual activity represented 0.07 to 0.09 percent of views, up from 0.06 to 0.08 percent in the previous quarter. The company took action on 21 million posts, about the same as the previous quarter. Hate speech. Facebook took action on 2.5 million posts for violating hate speech rules, up 56 percent from the previous quarter. Users reported 62 percent of hate speech posts before Facebook took action on them. Spam. Facebook took action on 837 million spam posts, up 15 percent from the previous quarter. The company says it detected nearly 100 percent of spam posts before users could report them. Fake accounts. Of Facebooks monthly users, 3 to 4 percent are fake accounts, the company said. It removed 583 million fake accounts in the first quarter of the year, down from 694 million in the previous quarter. The data, which the company plans to issue at least twice a year, is a move toward holding ourselves accountable, Facebook said in its report. This guide explains our methodology so the public can understand the benefits and limitations of the numbers we share, as well as how we expect these numbers to change as we refine our methodologies. Were committed to doing better, and communicating more openly about our efforts to do so, going forward. The company is still working to develop accurate metrics that describe how often hate speech is seen on the platform, said Guy Rosen, a vice president of product management, in an interview with reporters. The companys machine-learning systems have trouble identifying hate speech because computers have trouble understanding the context around speech. Theres a lot of really tricky cases, Rosen said. Is a slur being used to attack someone? Is it being used self-referentially? Or is it a completely innocuous term when its used in a different context? The final decisions on hate speech are made by human moderators, he added. Still, people post millions of unambiguously hateful posts to Facebook. In March, the United Nations said Facebook was responsible for spreading hatred of the Rohingya minority in Myanmar. Facebooks lack of moderators who speak the local language has hampered it in its effort to reduce the spread of hate speech. We definitely have to do more to make sure we pay attention to those, Rosen said, noting that the company had recently hired more moderators in the area. The enforcement report arrives a month after Facebook made its community standards public for the first time. The standards document what is and isnt allowed on Facebook, and serves as a guide for Facebooks global army of content moderators. Facebook is releasing its enforcement report at a time when the company is under increasing pressure to reduce hate speech, violence, and misinformation on its platform. Under pressure from Congress, Facebook has said it will double its safety and security team to 20,000 people this year.
As Facebook continues to grapple with spam, hate speech, and other undesirable content, the company is shedding more light on just how much content it is taking down or flagging each day. Facebook today published its first-ever Community Standards Enforcement Report, detailing what kind of action it took on content displaying graphic violence, adult nudity and sexual activity, terrorist propaganda, hate speech, and spam. Among the most noteworthy numbers: Facebook said that it took down 583 million fake accounts in the three months spanning Q1 2018, down from 694 million in Q4 2017. That doesnt include what Facebook says are millions of fake accounts that the company catches before they can finish registering. The report comes just a few weeks after Facebook published for the first time detailed internal guidelines for how it enforces content takedowns. The numbers give users a better idea of the sheer volume of fake accounts Facebook is dealing with. The company has pledged in recent months to use facial recognition technology — which it also uses to suggest which Facebook friends to tag in photos — to catch fake accounts that might be using another persons photo as their profile picture. But a recent report from the Washington Post found that Facebooks facial recognition technology may be limited when it comes to detecting fake accounts, as the tool doesnt yet scan a photo against all of the images posted by all 2.2 billion of the sites users to search for fake accounts. Facebook also gave a breakdown of how much other undesirable content it removed during Q1 2018, as well as how much of it was flagged by its systems or reported by users: The numbers show that Facebook is still predominately relying on other people to catch hate speech — which CEO Mark Zuckerberg has spoken about before, saying that its much harder to build an AI system that can determine what hate speech is then to build a system that can detect a nipple. Facebook defines hate speech as a direct attack on people based on protected characteristics — race, ethnicity, national origin, religious affiliation, sexual orientation, sex, gender, gender identity, and serious disability or disease. The problem is that, as Facebooks VP of product management Guy Rosen wrote in the blog post announcing todays report, AI systems are still years away from becoming effective enough to be relied upon to catch most bad content. But hate speech is a problem for Facebook today, as the companys struggle to stem the flow of fake news and content meant to encourage violence against Muslims in Myanmar has shown. And the companys failure to properly catch hate speech could push users off the platform before it is able to develop an AI solution. Facebook says it will continue to provide updated numbers every six months. The report published today spans from October 2017 to March 2018, with a breakdown comparing how much content the company took action on in various categories in Q4 2017 and Q1 2018.
It published a report on its community guideline enforcement efforts. Last month, Facebook published its internal community enforcement guidelines for the first time and today, the company has provided some numbers to show what that enforcement really looks like. In a new report that will be published quarterly, Facebook breaks down its enforcement efforts across six main areas -- graphic violence, adult nudity and sexual activity, terrorist propaganda, hate speech, spam and fake accounts. The report details how much of that content was seen by Facebook users, how much of it was removed and how much of it was taken down before any Facebook users reported it. Spam and fake accounts were the most prevalent and in the first quarter of this year, Facebook removed 837 million pieces of spam and 583 million fake accounts. Additionally, the company acted on 21 million pieces of nudity and sexual activity, 3.5 million posts that displayed violent content, 2.5 million examples of hate speech and 1.9 million pieces of terrorist content. In some cases, Facebook's automated systems did a good job finding and flagging content before users could report it. Its systems spotted nearly 100 percent of spam and terrorist propaganda, nearly 99 percent of fake accounts and around 96 percent of posts with adult nudity and sexual activity. For graphic violence, Facebook's technology accounted for 86 percent of the reports. However, when it came to hate speech, the company's technology only flagged around 38 percent of posts that it took action on and Facebook notes it has more work to do there. " As Mark Zuckerberg said at F8, we have a lot of work still to do to prevent abuse," Facebook's VP of product management, Guy Rosen, said in a post. "It's partly that technology like artificial intelligence, while promising, is still years away from being effective for most bad content because context is so important." Throughout the report, Facebook shares how the most recent quarter's numbers compare to those of the quarter before it, and where there are significant changes, it notes why that might be the case. For example, with terrorist propaganda, Facebook says its increased removal rate is due to improvements in photo detection technology that can spot both old and newly posted content. "This is a great first step," the Electronic Frontier Foundation's Jillian York told the Guardian. " However, we don't have a sense of how many incorrect takedowns happen -- how many appeals that result in content being restored. We'd also like to see better messaging to users when an action has been taken on their account, so they know the specific violation." "We believe that increased transparency tends to lead to increased accountability and responsibility over time, and publishing this information will push us to improve more quickly too," wrote Rosen. "This is the same data we use to measure our progress internally -- and you can now see it to judge our progress for yourselves. We look forward to your feedback."
Facebook this morning released its latest Transparency report, where the social network shares information on government requests for user data, noting that these requests had increased globally by around 4 percent compared to the first half of 2017, though U.S. government-initiated requests stayed roughly the same. In addition, the company added a new report to accompany the usual Transparency report, focused on detailing how and why Facebook takes action on enforcing its Community Standards, specifically in the areas of graphic violence, adult nudity and sexual activity, terrorist propaganda, hate speech, spam and fake accounts. In terms of government requests for user data, the global increase led to 82,341 requests in the second half of 2017, up from 78,890 during the first half of the year. U.S. requests stayed roughly the same at 32,742; though 62 percent included a non-disclosure clause that prohibited Facebook from alerting the user – thats up from 57 percent in the earlier part of the year, and up from 50 percent from the report before that. This points to use of the NDA becoming far more common among law enforcement agencies. The number of pieces of content Facebook restricted based on local laws declined during the second half of the year, going from 28,036 to 14,294. But this is not surprising – the last report had an unusual spike in these sort of requests due to a school shooting in Mexico, which led to the government asking for content to be removed. There were also 46 46 disruptions of Facebook services in 12 countries in the second half of 2017, compared to 52 disruptions in nine countries in the first half. And Facebook and Instagram took down 2,776,665 pieces of content based on 373,934 copyright reports, 222,226 pieces of content based on 61,172 trademark reports and 459,176 pieces of content based on 28,680 counterfeit reports. However, the more interesting data this time around comes from a new report Facebook is appending to its Transparency report, called the Community Standards Enforcement Report which focuses on the actions of Facebooks review team. This is the first time Facebook has released its numbers related to its enforcement efforts, and follows its recent publication of its internal guidelines three weeks ago. In 25 pages, Facebook in April explained how it moderates content on its platform, specifically around areas like graphic violence, adult nudity and sexual activity, terrorist propaganda, hate speech, spam and fake accounts. These are areas where Facebook is often criticized when it screws up – like when it took down the newsworthy Napalm Girl historical photo because it contained child nudity, before realizing the mistake and restoring it. It has also been more recently criticized for contributing to Myanmar violence, as extremists hate speech-filled posts incited violence. This is something Facebook also today addressed through an update for Messenger, which now allows users to report conversations that violate community standards. Todays Community Standards report details the number of takedowns across the various categories it enforces. Facebook says that spam and fake account takedowns are the largest category, with 837 million pieces of spam removed in Q1 – almost all proactively removed before users reported it. Facebook also disabled 583 million fake accounts, the majority within minutes of registration. During this time, around 3-4 percent of Facebook accounts on the site were fake. The company is likely hoping the scale of these metrics makes it seem like its doing a great job, when in reality, it didnt take that many Russian accounts to throw Facebooks entire operation into disarray, leading to CEO Mark Zuckerberg testifying before a Congress thats now considering regulations. In addition, Facebook says it took down the following in Q1 2018: You may notice that one of those areas is lagging in terms of enforcement and automation. Facebook, in fact, admits that its system for identifying hate speech still doesnt work that well, so it needs to be checked by review teams. … we have a lot of work still to do to prevent abuse, writes Guy Rosen, VP of Product Management, on the Facebook blog. Its partly that technology like artificial intelligence, while promising, is still years away from being effective for most bad content because context is so important. In other words, A.I. can be useful at automatically flagging things like nudity and violence, but policing hate speech requires more nuance than the machines can yet handle. The problem is that people may be discussing sensitive topics, but theyre doing it to share news, or in a respectful manner, or even describing something that happened to them. Its not always a threat or hate speech, but a system only parsing words without understanding the full discussion doesnt know this. To get an A.I. system up to par in this area, it requires a ton of training data. And Facebook says it doesnt have that for some of the less widely-used languages. (This is also a likely response to the Myanmar situation, where the company belatedly – after six civil society organizations, criticized Mr. Zuckerberg in a letter – said it had hired dozens of human moderators. Critics say thats not enough – in Germany, for example, which has strict laws around hate speech – Facebook hired about 1,200 moderators, The NYT said.) It seems the obvious solution is staffing up moderation teams everywhere, until A.I. technology can do as good of a job as it can on other aspects of content policy enforcement. This costs money, but its also clearly critical when people are dying as a result of Facebooks lacking ability to enforce its own policies. Facebook claims its hiring as a result, but doesnt share the details of how many, where or when. …were investing heavily in more people and better technology to make Facebook safer for everyone wrote Rosen. But Facebooks main focus, it seems, is on improving technology. Facebook is investing heavily in more people to review content that is flagged. But as Guy Rosen explained two weeks ago, new technology like machine learning, computer vision and artificial intelligence helps us find more bad content, more quickly – far more quickly, and at a far greater scale, than people ever can, said Alex Schultz, Vice President of Analytics, in a related post on Facebooks methodology. He touts A.I. in particular as being a tool that could get content off Facebook before its even reported. But A.I. isnt ready to police all hate speech yet, so Facebook needs a stop gap solution – even if it costs.