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.
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.