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Facebook’s new authorization process for political ads goes live in the US

Earlier this month — and before Facebook CEO Mark Zuckerberg testified before Congress — the company announced a series of changes to how it would handle political advertisements running on its platform in the future. It had said that people who wanted to buy a political ad — including ads about political “issues” — would have to reveal their identities and location and be verified before the ads could run. Information about the advertiser would also display to Facebook users.

Today, Facebook is announcing the authorization process for U.S. political ads is live.

Facebook had first said in October that political advertisers would have to verify their identity and location for election-related ads. But in April, it expanded that requirement to include any “issue ads” — meaning those on political topics being debated across the country, not just those tied to an election.

Facebook said it would work with third parties to identify the issues. These ads would then be labeled as “Political Ads,” and display the “paid for by” information to end users.

According to today’s announcement, Facebook will now begin to verify the identity and the residential mailing address of advertisers who want to run political ads. Those advertisers will also have to disclose who’s paying for the ads as part of this authorization process.

This verification process is currently only open in the U.S. and will require Page admins and ad account admins to submit their government-issued ID to Facebook, along with their residential mailing address.

The government ID can either be a U.S. passport or U.S. driver’s license, a FAQ explains. Facebook will also ask for the last four digits of admins’ Social Security Number. The photo ID will then be approved or denied in a matter of minutes, though anyone declined based on the quality of the uploaded images won’t be prevented from trying again.

The address, however, will be verified by mailing a letter with a unique access code that only the admin’s Facebook account can use. The letter may take up to 10 days to arrive, Facebook notes.

Along with the verification portion, Page admins will also have to fill in who paid for the ad in the “disclaimer” section. This has to include the organization(s) or person’s name(s) who funded it.

This information will also be reviewed prior to approval, but Facebook isn’t going to fact check this field, it seems.

Instead, the company simply says: “We’ll review each disclaimer to make sure it adheres to our advertising policies. You can edit your disclaimers at any time, but after each edit, your disclaimer will need to be reviewed again, so it won’t be immediately available to use.”

The FAQ later states that disclaimers must comply with “any applicable law,” but again says that Facebook only reviews them against its ad policies.

“It’s your responsibility as the advertiser to independently assess and ensure that your ads are in compliance with all applicable election and advertising laws and regulations,” the documentation reads.

Along with the launch of the new authorization procedures, Facebook has released a Blueprint training course to guide advertisers through the steps required, and has published an FAQ to answer advertisers’ questions.

Of course, these procedures will only net the more scrupulous advertisers willing to play by the rules. That’s why Facebook had said before that it plans to use AI technology to help sniff out those advertisers who should have submitted to verification, but did not. The company is also asking people to report suspicious ads using the “Report Ad” button.

Facebook has been under heavy scrutiny because of how its platform was corrupted by Russian trolls on a mission to sway the 2016 election. The Justice Department charged 13 Russians and three companies with election interference earlier this year, and Facebook has removed hundreds of accounts associated with disinformation campaigns.

While tougher rules around ads may help, they alone won’t solve the problem.

It’s likely that those determined to skirt the rules will find their own workarounds. Plus, ads are only one of many issues in terms of those who want to use Facebook for propaganda and misinformation. On other fronts, Facebook is dealing with fake news — including everything from biased stories to those that are outright lies, intending to influence public opinion. And of course there’s the Cambridge Analytica scandal, which led to intense questioning of Facebook’s data privacy practices in the wake of revelations that millions of Facebook users had their information improperly accessed.

Facebook says the political ads authorization process is gradually rolling out, so it may not be available to all advertisers at this time. Currently, users can only set up and manage authorizations from a desktop computer from the Authorizations tab in a Facebook Page’s Settings.

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As Facebook shapes our access to information, Twitter dictates public opinion and Tinder influences our dating decisions, the algorithms we’ve developed to help us navigate choice are now actively driving every aspect of our lives. But as we increasingly rely on them for everything from how we seek out news to how we relate to the people around us, have we automated the way we behave? Is human thinking beginning to mimic algorithmic processes? And is the Cambridge Analytica debacle a warning sign of what’s to come — and of happens when algorithms hack into our collective thoughts? It wasn’t supposed to go this way. Overwhelmed by choice — in products, people and the sheer abundance of information coming at us at all times — we’ve programmed a better, faster, easier way to navigate the world around us. Using clear parameters and a set of simple rules, algorithms help us make sense of complex issues. They’re our digital companions, solving real-world problems we encounter at every step, and optimizing the way we make decisions. What’s the best restaurant in my neighborhood? Google knows it. How do I get to my destination? Apple Maps to the rescue. What’s the latest Trump scandal making the headlines? Facebook may or may not tell you. Wouldn’t it be nice if code and algorithms knew us so well — our likes, our dislikes, our preferences — that they could anticipate our every need and desire? That way, we wouldn’t have to waste any time thinking about it: We could just read the one article that’s best suited to reinforce our opinions, date whoever meets our personalized criteria and revel in the thrill of familiar surprise. Imagine all the time we’d free up, so we could focus on what truly matters: carefully curating our digital personas and projecting our identities on Instagram. It was Karl Marx who first said our thoughts are determined by our machinery, an idea that Ellen Ullman references in her 1997 book, Close to the Machine, which predicts many of the challenges we’re grappling with today. Beginning with the invention of the internet, the algorithms we’ve built to make our lives easier have ended up programming the way we behave. Photo courtesy of Shutterstock/Lightspring Here are three algorithmic processes and the ways in which they’ve hacked their way into human thinking, hijacking our behavior. Product comparison: From online shopping to dating Amazon’s algorithm allows us to browse and compare products, save them for later and eventually make our purchase. But what started as a tool designed to improve our e-commerce experience now extends much beyond that. We’ve internalized this algorithm and are applying it to other areas of our lives — like relationships. Dating today is much like online shopping. Enabled by social platforms and apps, we browse endless options, compare their features and select the one that taps into our desires and perfectly fits our exact personal preferences. Or just endlessly save it for later, as we navigate the illusion of choice that permeates both the world of e-commerce and the digital dating universe. Online, the world becomes an infinite supply of products, and now, people. “The web opens access to an unprecedented range of goods and services from which you can select the one thing that will please you the most,” Ullman explains in Life in Code. “[There is the idea] that from that choice comes happiness. A sea of empty, illusory, misery-inducing choice.” We all like to think that our needs are completely unique — and there’s a certain sense of seduction and pleasure that we derive from the promise of finding the one thing that will perfectly match our desires. Whether it’s shopping or dating, we’ve been programmed to constantly search, evaluate and compare. Driven by algorithms, and in a larger sense, by web design and code, we’re always browsing for more options. In Ullman’s words, the web reinforces the idea that “you are special, your needs are unique, and [the algorithm] will help you find the one thing that perfectly meets your unique need and desire.” In short, the way we go about our lives mimics the way we engage with the Internet. Algorithms are an easy way out, because they allow us to take the messiness of human life, the tangled web of relationships and potential matches, and do one of two things: Apply a clear, algorithmic framework to deal with it, or just let the actual algorithm make the choice for us. We’re forced to adapt to and work around algorithms, rather than use technology on our terms. Which leads us to another real-life phenomenon that started with a simple digital act: rating products and experiences. Quantifying people: Ratings & reviews As with all other well-meaning algorithms, this one is designed with you and only you in mind. Using your feedback, companies can better serve your needs, provide targeted recommendations just for you, and serve you more of what you’ve historically shown to like, so you can carry on mindlessly consuming it. From your Uber ride to your Postmate delivery to your Handy cleaning appointment, nearly every real-life interaction is rated on a scale of 1-5 and reduced to a digital score. As a society we’ve never been more concerned with how we’re perceived, how we perform, and how we compare to others’ expectations. We’re suddenly able to quantify something as subjective as our Airbnb host’s design taste or cleanliness. And the sense of urgency with which we do it is incredible — you’re barely out of your Uber car when you neurotically tap all five stars, tipping with wild abandon in a quest to improve your passenger rating. And the rush of being reviewed in return! It just fills you with utmost joy. Yes, you might be thinking of that dystopian Black Mirror scenario, or that oddly relatable Portlandia sketch, but we’re not too far off from a world where our digital score simultaneously replaces and drives all meaning in our lives. We’ve automated the way we interact with people, where we’re constantly measuring and optimizing those interactions in an endless cycle of self-improvement. It started with an algorithm, but it’s now second nature. As Jaron Lainier wrote in his introduction to Close to the Machine, “We create programs using ideas we can feed into them, but then [as] we live through the program. . .we accept the ideas embedded in it as facts of nature.” That’s because technology makes abstract and often elusive, desirable qualities quantifiable. Through algorithms, trust translates into ratings and reviews, popularity equals likes, and social status means followers. Algorithms create a sort of Baudrillardian simulation, where each rating has completely replaced the reality it refers to, and where the digital review feels more real, and certainly more meaningful, than the actual, real-life experience. In facing the complexity and chaos of real life, algorithms help us find ways to simplify it; to take the awkwardness out of social interaction and the insecurity that comes with opinions and real-life feedback, and make it all fit neatly into a ratings box. But as we adopt programming language, code, and algorithms as part of our own thinking, are human nature and artificial intelligence merging into one? We’re used to think of AI as an external force, something we have little control over. What if the most immediate threat of AI is less about robots taking over the world, and more about technology becoming more embedded into our consciousness and subjectivity? In the same way that smartphones became extensions of our senses and our bodies, as Marshall McLuhan might say, algorithms are essentially becoming extensions of our thoughts. But what do we do when when they replace the very qualities that make us human? And, as Lainier asks, “As computers mediate human language more and more over time, will language itself start to change?” Image: antoniokhr/iStock Automating language: Keywords and buzzwords Google indexes search results based on keywords. SEO makes websites rise to the top of search results, based on specific tactics. To achieve this, we work around the algorithm, figure out what makes it tick, and sprinkle websites with keywords that make it more likely to stand out in Google’s eyes. But much like Google’s algorithm, our mind prioritizes information based on keywords, repetition, and quick cues. It started as a strategy we built around technology, but it now seeps into everything we do–from the the way we write headlines to how we generate “engagement” with our tweets to how we express ourselves in business and everyday life. Take the buzzword mania that dominates both the media landscape and the startup scene. A quick look at some of the top startups out there will show that the best way to capture people’s attention–and investors’ money–is to add “AI,” “crypto” or “blockchain” into your company manifesto. Companies are being valuated based on what they’re signifying to the world through keywords. The buzzier the keywords in the pitch deck, the higher the chances a distracted investor will throw some money at it. Similarly, a headline that contains buzzwords is far more likely to be clicked on, so the buzzwords start outweighing the actual content. Clickbait being one symptom of that. Where do we go from here? Technology gives us clear patterns; online shopping offers simple ways to navigate an abundance of choice. Therefore there’s no need to think — we just operate under the assumption that algorithms know best. We don’t exactly understand how they work, and that’s because code is hidden: we can’t see it, the algorithm just magically presents results and solutions. As Ullman warns in Life in Code, “When we allow complexity to be hidden and handled for us, we should at least notice what we are giving up. We risk becoming users of components. . .[as we] work with mechanisms that we do not understand in crucial ways. This not-knowing is fine while everything works as expected. But when something breaks or goes wrong or needs fundamental change, what will we do except stand helpless in the face of our own creations?” Cue fake news, misinformation, and social media targeting in the age of Trump. Image courtesy of Intellectual Take Out. So how do we encourage critical thinking, how do we spark more interest in programming, how do we bring back good old-fashioned debate and disagreement? What can we do to foster difference of opinion, let it thrive, and allow it to challenge our views? When we operate within the bubble of distraction that technology creates around us, and when our social media feeds consist of people who think just like us, how can we expect social change? What ends up happening is we operate exactly as the algorithm intended us to. The alternative is questioning the status quo, analyzing the facts and arriving at our own conclusions. But no one has time for that. So we become cogs in the Facebook machine, more susceptible to propaganda, blissfully unaware of the algorithm at work–and of all the ways in which it has inserted itself into our thought processes. As users of algorithms rather than programmers or architects of our own decisions, our own intelligence become artificial. It’s “program or be programmed” as Douglas Rushkoff would say. If we’ve learned anything from Cambridge Analytica and the 2016 U.S. elections, it’s that it is surprisingly easy to reverse-engineer public opinion, to influence outcomes, and to create a world where data, targeting, and bots lead to a false sense of consensus. What’s even more disturbing is that the algorithms we trust so much–the ones that are deeply embedded in the fabric of our lives, driving our most personal choices–continue to hack into our thought processes, in increasingly bigger and more significant ways. And they will ultimately prevail in shaping the future of our society, unless we reclaim our role as programmers, rather than users of algorithms.

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