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 – that’s 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 Facebook’s 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.
Today’s 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 it’s doing a great job, when in reality, it didn’t take that many Russian accounts to throw Facebook’s entire operation into disarray, leading to CEO Mark Zuckerberg testifying before a Congress that’s now considering regulations.
In addition, Facebook says it took down the following in Q1 2018:
- Adult Nudity and Sexual Activity: 21 million pieces of content; 96 percent was found and flagged by technology, not people
- Graphic violence: took down or added warning labels to 3.5 million pieces of content; 86 percent found and flagged by technology
- Hate speech: 2.5 million pieces of content, 38 percent found and flagged by technology
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 doesn’t 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. “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.”
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 they’re doing it to share news, or in a respectful manner, or even describing something that happened to them. It’s not always a threat or hate speech, but a system only parsing words without understanding the full discussion doesn’t 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 doesn’t 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 that’s 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 it’s also clearly critical when people are dying as a result of Facebook’s lacking ability to enforce its own policies.
Facebook claims it’s hiring as a result, but doesn’t share the details of how many, where or when.
“…we’re investing heavily in more people and better technology to make Facebook safer for everyone” wrote Rosen.
But Facebook’s 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 Facebook’s methodology.
He touts A.I. in particular as being a tool that could get content off Facebook before it’s even reported.
But A.I. isn’t ready to police all hate speech yet, so Facebook needs a stop gap solution – even if it costs.