Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity (5 page)

So in spite of its interactive patina, the digital economy continues the industrial practice of preventing real people from participating in the growth economy—at least as its beneficiaries. We still get to work, and we still end
up living and socializing on a landscape that feels much more like business than pleasure. There’s just no money.

In fact, the digital landscape so effectively monopolizes economic activity that most people have almost nothing left to be extracted. That’s why in order to maintain some semblance of growth, Internet companies had to find a way to monetize something other than cash from its users. Something measurable, countable, and attractive enough to shareholders to justify their real cash investment in the companies’ stock.

That’s right: “likes.”

Social media originally appeared to be an alternative to the marketplace ethos of the dot-com era. After the dot-com boom and bust, fledgling social platforms such as Friendster, Blogger, and Myspace seemed to be offering a return to the more peer-to-peer sensibility of the early Internet. But the alternative value systems they created—likes, views, reblogs, favorites, and so on—became a new kind of currency. It’s more than a mere trend in marketing styles away from broadcast advertising toward peer-to-peer social influence. It amounts to a shift in the way we value everything from entertainment and culture to consumer goods and the stock market. Likes are a new way to stoke the growth furnace.

Likes themselves are a metric of worth—and not just for teenagers gauging their social status. Real companies are valued in terms of the likes they can generate. Brands from soft drinks to automobiles check their social media traffic for upticks on a daily if not hourly basis. A multitude of sweepstakes ask consumers to do nothing more than like or retweet an ad for a chance to win cash and other prizes. According to research conducted mostly by social media companies, these “social” recommendations—particularly from trusted “friends”—mean a whole lot more than plain advertisements.

The economy of likes is most important to the social media companies themselves. At the time of its billion-dollar purchase by Facebook, Instagram had raised $57.5 million, was valued at $500 million, and had generated $0 in revenue.
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It did, however, boast 49.6 million likes per day,
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which has grown to 1.2 billion in the ensuing year and a half.
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Likewise, Tumblr netted negative $13 million the year it was purchased by Yahoo for $1.1 billion.
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What it lost in earnings it made up for in social traffic of 900 posts/second.
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Snapchat, a social media app with no revenue, turned down a $3 billion offer from Facebook—all for its users’ 400 million daily, dissolving pings.
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Whether or not all that social activity will someday generate true, sustainable profits is still left to be seen. What we do know is that the likes, follows, favorites, and reposts are not as immediately valuable to the people and things being liked as they are to the companies who mine these big data troves for trends. In fact, social media companies such as Facebook now occasionally surprise Wall Street analysts by reporting revenue vastly in excess of their expectations. That’s because the analysts are still thinking in terms of advertising dollars. The real revenue stream has much less to do with display ads than it does with the data that social media companies can glean from everyone’s friending and liking—information that social media companies sell to big data market research firms such as Acxiom, Claritas, and Datalogix.

But if social media companies are going to maintain their growth, they must continue to generate more and more likes out of us humans. Since they can’t take any more of our money, all these social media platforms must by their very nature harvest an increasingly large share of our attention, our time, and our data.

Users are only slowly coming to grips with the fact that they are not Facebook’s customers but its product. Many Americans reacted in horror to the news that Facebook was conducting psychological experiments on its users.
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But if they’d had any real awareness of how the company earns revenue, they shouldn’t have been surprised at all. Facebook was simply attempting to show that the kinds of emotional contagion that occur in real life also happen online. Their social scientists proved that if people see a bunch of happy posts, they are more likely to make happy posts themselves. The controversy over the invasion of privacy or psychological manipulation may really just be displaced anxiety: we are just scared to see human emotion and action so successfully simulated and stimulated
by machines. For Facebook proved that it had re-created human relationships but in the completely controlled setting of an online platform.

It’s back to the medieval bazaar, except without the unpredictability of real human contact. It’s a race for likes—a value system rigged from the beginning to reward one’s volume of friendships over their quality. The more we depend on these numbers, the less truly social we become. While industrial-age processes simply removed human beings from the equation, these digital processes seek to
simulate
humanity through artificial social media. As digital consumers, we are no longer engaging with humans but with metrics. Life becomes one big power-law distribution.

This is just where the winners of the digital industrial economy want to keep things. Trust your “friends” and trust the numbers. Experts be damned. Reviews by
Consumer Reports
, where real scientists in expensive laboratories conduct meticulous experiments on products, are to be ignored in favor of free “peer” recommendations from strangers.
Professional
is just another way of saying
elitist,
anyway. Who needs a real review when you can just see how many people “like” something, instead? Market extremes otherwise dampened by expertise instead spin wildly out of control, while real-world professional experts, journalists, editors, and reviewers lose their jobs. An increasing number of job categories are challenged by the Internet ethos of free and open exchange among all those people on the skinny, profitless expanse of the power-law curve.

Social media companies grow at the expense of their users.

As if responding to this obvious critique of his Long Tail theory, Chris Anderson followed up with a book called
Free,
arguing that we should all give away our labor and products. In his view, creative professionals in particular should welcome the opportunity to give away their books, music, and other products because they build up demand for other services such as live performances and lectures. “Those $20k speaker fees soon add up,”
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he explains. Of course, the only venues capable of paying those fees are corporations looking for speakers to validate their practices and reinforce the cycle of dehumanization—not schools and communities seeking help in resisting those forces.

Musicians, meanwhile, are supposed to sign “360 deals,” named for the idea that they are agreeing to let a single corporation manage all their recordings, performances, merchandise, product placements, and residuals. Albums may not generate much income, but a sold-out concert can. Only now, that concert needs to be supported by a steady flow of online media and new releases.
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According to industry expert Bob Lefsetz, musicians have to give up the quaint notion of sitting around in a studio for a year developing an album.
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The album won’t make money, anyway. Musicians’ new job is to develop a constant flow of fresh content to an audience that will forget them in a few months if they don’t. It’s all singles, and all designed to get and stay on the iTunes list and Pandora rotation—which themselves don’t generate even a fraction of the revenue musicians used to collect off album sales. That money comes only from going on the road, and only if you are a superstar.

For the rest of us, the math of “free” doesn’t quite add up, unless we happen to own the platform. Those of us who wrote for the Huffington Post for years did so because we felt we were contributing to a progressive community platform. No, we were not paid in dollars, but there was a sense of solidarity in supporting a new kind of journalism, and a mutually reinforcing credibility when we all participated. When Arianna Huffington went on to sell the entire enterprise to AOL for $315 million, she did not cut her nine thousand unpaid writers in on the winnings.
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It was as if by receiving exposure on the Web site’s pages, we were already the beneficiaries of Arianna’s largesse.

In reality, Arianna wasn’t selling a profitable business in the traditional sense. The Huffington Post was poor in cash but rich in likes and follows. That’s what she was selling. And that’s what many of us are learning to sell, too. For it’s not the people or their work that matter but the data their activities generate. This stuff—these likes—are not an entirely phantom metric used to fool shareholders. They are worth real money, either to brands that want to become “friends” with the fans of a particular celebrity or, better, to market researchers who want to gather data about a particular demographic.

In a landscape dominated by social media, everything begins to matter less for what it is than for how many likes it can generate—because more likes means more data to sell. The music, movies, and TV shows that entertainers create matter less to their careers than the volume of social media activity they can drum up around them. Rock videos and TV series are cast based on the number of followers a star can bring along with her. Artists and entertainers are no longer performing for human audiences so much as for the big data computers. Nursing one’s Twitter or Instagram following is compulsory. Instead of taking acting lessons, the aspiring star must stir up social media attention and keep feeding users more content in order to draw out more likes from them. Given the way attention works online, this means resorting to the least-common-denominator antics: wardrobe malfunctions, sex tapes, and other usually degrading sensationalism.

Cultural judgments aside, this online social climbing leads to a strangely circular career path: creators must develop social media networks in order to “make it.” But then once they’ve made it, the main thing they have to sell is not whatever talent they’ve come with but the social media network they have amassed. Yes, a famous rock star can still make money on a tour, just as a TV star gets paid for appearing on a sitcom. But these jobs are really just fodder for the bigger prize of becoming a media property oneself. Just as Arianna did.

There is a certain, if limited, empowerment in all this. A large factor in making it as a performer or even a journalist was always the ability to generate advertising revenue. In traditional media, the advertiser could dictate to TV networks and newspaper editors. If a show didn’t somehow serve the advertiser, it was pulled. Likewise, the entire notion of “unbiased” journalism emerged only after national brands demanded neutral backdrops for their advertisements, so they wouldn’t be accused of backing one side. By working their own social networks, creators no longer have “the man” looking over their shoulder. The new solution is to
become
“the man.”

“You are your own media company,” Oliver Luckett, founder of the
first real social media talent and marketing agency, theAudience, explained to me when I pressed him on it. “One hundred percent. That is every single person’s goal in this.” Working with online celebrities from Ian Somerhalder and Steve Aoki to Russell Brand and Pitbull—people with multiple millions of followers and likes—Luckett uses a social data analysis platform to match his clients’ social networks with the right brands. So if 10 percent of a TV star’s million followers have also engaged with a particular shampoo or automobile brand on social media, Luckett is armed with data that can win his client a new social media endorsement. Likes for sale.
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Pop stars like Jay Z take it to a new level, distributing free music apps that log users’ contacts, geolocation, and even phone records, all to scrape more user data,
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which is in turn sold to advertisers and market researchers. It’s as if no matter what business you’re in, profit ultimately rests on your ability to glean and sell the data associated with your transactions. Even on e-commerce sites, in many cases the profitability of retail transactions pales in comparison with that of the big data they leave in their wake. Creating relationships with consumers is really just about engendering enough trust to get them to share their data assets with you.

Artists, publishers, newspapers, entertainers, and cultural producers of all sorts will have to be tuned to, if not entirely geared toward, reaching easily identified social audiences. This is not a soft science, like determining a printed magazine’s audience in the old days. It’s hard data on engagement. As an author, my books will be less valuable as objects for sale (people won’t be paying for things like books anymore, anyway) than as the publishing tool through which I accumulate followers on social networks, whom I then sell to brands. So my books had better be brand-friendly and my audiences preselected for their data-richness. And even then I’ll have to make it to the very head of the long tail to be of interest. Even social media deserves a better role in our lives and businesses than this.

The unsustainable endgame is an economy based entirely on marketing and advertising. In its currently inflated state, the entirety of advertising, marketing, public relations, and associated research still accounts for less
than 5 percent of gross domestic product (GDP), by the very most generous estimates.
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Furthermore, unscrupulous Web site owners have now learned to use robotic ad-viewing programs to juice their revenue from pay-per-click advertising. Most of these bot programs run secretly on the computers of everyday users in the form of malware, a kind of minivirus that co-opts a computer’s processing power. Bots now comprise an estimated 25 percent of all online video ad viewers and 10 percent of all static display ads. In 2015, advertisers are projected to lose $6.3 billion in pay-per-click fees to these imaginary viewers.
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Consider the irony: malware robots watch ads, monitored by automated tracking software that tailors each advertising message to suit the malbots’ automated habits, in a human-free feedback loop of ever-narrowing “personalization.” Nothing of value is created, but billions of dollars are made.