Livia Gershon | Longreads | April 2019 | 9 minutes (2,270 words)
When I was a kid, in the pre-internet days of the 1980s, my screen time was all about Nickelodeon. My favorite show was “You Can’t Do That on Television.” It was a kind of sketch show; the most common punchline was a bucket of green slime being dropped on characters’ heads. It was pretty dumb. It was also created by professional writers, actors, and crew, who were decently paid; many of them belonged to unions.
Today, my kids don’t have much interest in that sort of show. For them, TV mostly means YouTube. Their preferred channels collect memes and jokes from various corners of the internet. In a typical show, a host puts on goofy voices to read posts from r/ChoosingBeggars, a Reddit message board devoted to customers who make absurd demands of Etsy vendors. It’s significantly funnier than “You Can’t Do That on Television,” I admit. It also involves no unionized professionals.
The production of the shows my kids enjoy goes something like this: Unpaid redditors post original material to amuse their online friends. Unpaid moderators keep the subreddit functioning by cleaning out spam and abuse. Reddit gets a little money from ads posted on the subreddit. Then a YouTube channel called Sorrow TV—apparently a one-man operation run by a 20-something guy—harvests the best posts and creates the video. YouTube, which is part of Google, runs more ads, while collecting valuable data about the viewing patterns of users like my kids. YouTube shares some of the money it makes with SorrowTV, based on a formula that Google controls and can alter at any time.
Today’s media is ruled by a handful of corporations with enormous market power. One thing that makes these companies so valuable is how few people they employ, relatively speaking, for each dollar earned. A New York Times analysis last year found that Facebook makes just a hair under $635,000 in profit for each of its 25,000 employees. Alphabet, Google’s parent company, makes about $158,000 per worker. (At Walmart, it’s $4,288.) These calculations often get spun as representing a victory for automation and algorithms—machines, rather than humans, creating value. But the truth is, these media companies have billions of people working for them—they’re just not on staff. Whenever you post a photo on Instagram, write an Amazon review, or skim through complaints about potholes on your neighborhood’s Facebook group, you’re helping generate profit for the world’s richest corporations. A growing movement is making the case that you ought to get paid for it.
Typically, we don’t think of social media use as labor. Finding your way with Google Maps seems (particularly to those of us old enough to remember planning a trip with paper maps) like a luxurious free service. Keeping up with distant friends on Facebook feels like recreation. Answering questions on Yelp about whether the library you just visited has a wheelchair ramp is like a tiny public service.
But, of course, these companies aren’t providing anything for free. In Radical Markets (2017), Eric A. Posner, a law professor at the University of Chicago, and E. Glen Weyl, a senior researcher at Microsoft Research and visiting scholar at Princeton University, make the case that companies should pay for the information they collect from us. They point to Big Tech’s use of our data, not just to choose what ads we’ll see—or to sell to questionable political targeting operations—but also to create new technology. Facebook and Instagram (a Facebook property) use the images and videos we upload to power machine learning. That’s where new artificial intelligence products like face recognition and automated video editing come from. Translating a photo caption for your friends helps teach Google Translate how languages work. When you click the boxes on ReCAPTCHA, the ubiquitous anti-spam tool owned by Google, it helps computers learn to digitize text and—probably—improves self-driving car technology.
A growing movement is making the case that you ought to get paid for your social media posts.
How big a deal this is for the economy depends on how successful artificial intelligence will be in replacing workers over the coming decades. “As the digital sector grows, it could wind up being very large,” Weyl told me. In fact, he said, treating data as labor could help AI technology develop faster—companies would be able to explicitly ask us for the information they need rather than trick us into providing it. But that would mean that they’d have to divvy up the spoils. “These companies have addicted themselves so much to being labor light,” Weyl said. “It’s impacting AI’s ability to make a broad impact on the economy.”
Writing in the Harvard Business Review with Jaron Lanier, a prominent critic of social media, Weyl argues that if Americans were paid for our data, many would make $500 to $1,000 a year the way things stand now (an estimate that the authors believe is low). If AI were to grow to represent 10 percent of the U.S. economy, Weyl and Lanier add, that amount could rise to $20,000 for an average family of four—though in that information economy, we’d all pay a little more for the services we use.
Even absent economically powerful machine learning, companies benefit in a variety of ways from the work we do for free online—including in the least profit-driven settings. Dorothy Howard, a Ph.D. student and digital labor scholar at the University of California San Diego, became interested in digital labor while volunteering for Wikipedia. “I was spending a lot of time editing and moderating and helping to solve disputes, and then also doing some diversity work, organizing around Wikipedia’s gender gap,” she said. “I developed some burnout. I felt really exhausted.”
Howard began researching burnout among activists and volunteers and soon ran into feminist critiques of traditionally unpaid women’s work. Howard pointed me to “Wages for Facebook,” a project created in 2014 by Laurel Ptak, a curator and visual artist. The project’s name is a twist on Wages for Housework, a radical 1970s feminist assault on the idea of housework as an extension of natural, nurturing womanhood. More than a practical demand for payment, Wages for Housework tried to recast domestic life as unpaid, unacknowledged labor that contributed to capitalism by making men’s paid work possible.
Echoing “Wages Against Housework,” a classic 1975 essay by Silvia Federici, a feminist theorist, Ptak designed a website, Wages for Facebook, with bold, all-caps text that scrolls down readers’ screens. “By denying our Facebook time a wage while profiting directly from the data it generates and transforming it into an act of friendship, capital has killed many birds with one stone,” it reads. “First of all, it has got a hell of a lot of work almost for free, and it has made sure that we, far from struggling against it, would seek that work as the best thing online.”
Wikipedia is a nonprofit, and a much-cited example of the utopian promise of collective online work. Still, Howard argues, anything produced online serves to the advantage of big tech companies. “Wikipedia seeds the Google knowledge engine,” she told me. “Licensing is so open, contributing to Wikipedia also means you’re creating this knowledge that could be used in a number of other settings.”
That’s also true of many other voluntary and collective online enterprises, including open source software projects. The most significant of these is probably Linux, a slightly modified version of which helps power Google’s Android operating system, the core of Amazon Web Services, and servers that host the vast majority of the world’s websites. “The project itself is really committed to the politics of making code freely available for anyone to use, and the volunteers are committed to that,” Howard said. “That creates resources for companies to use.”
Entertainment companies take advantage of another type of free labor: the work of fans. Producers of movies, TV shows, and other projects often lean heavily on fans to act as vast, informal focus groups, and to promote their products. “Paid advertisements used to fill that sort of role,” Mel Stanfill, a digital media scholar at the University of Central Florida and the author of Exploiting Fandom (2019), told me. “To whatever extent that’s been pulled back, that’s monetary gain.”
Devoted fans are more likely than casual social media users to think of their efforts as real work. But Stanfill said that they still don’t necessarily want wages. For them, creating interesting stories, videos, or memes—or promoting and supporting others’ work—is a source of status. “There’s two economies happening at the same time,” Stanfill explained. “There’s the market economy where these activities are valuable labor, but there’s also what people refer to as the gift economy where people are producing things as expressions of love.”
Sometimes the two economies clash dramatically, as in the case of “Serenity,” a science fiction movie from 2005 based on “Firefly,” a cult TV show. Universal Studios unleashed a marketing campaign that revolved around fans’ work—enthusiasts organized viewing sessions, posted about the movie online, and created art using the official movie logo. A year later, however, Universal turned on fan artists, in one case threatening the owner of a Café Press store selling “Serenity”-themed merchandise with a retroactive $8,750 licensing fee and statutory damages of up to $150,000 per infringed work. Fans responded by drawing up an invoice covering the hours they had spent promoting the movie. The figure they came up with, for some 28,000 hours, was more than $2.1 million.
The fans acknowledged in their statement that they weren’t really expecting to collect cash. “We just believe that there is a point to be made,” they wrote. The development and enforcement of copyright law consistently favors wealthy companies over individuals. Still, Stanfill told me, “It’s a huge power imbalance that has to be resolved somehow.”
Fans drew up an invoice covering the time they had spent promoting the movie: 28,000 hours for $2.1 million.
Fans are trying to gain recognition. A prominent example is the Organization for Transformative Works (OTW), a fan-run nonprofit that was founded in 2007. One of its projects, An Archive of Our Own, recently received a Hugo Award nomination for its work hosting nearly five million pieces of fan fiction and art, catering to the needs of fans rather than entertainment companies. OTW also does legal advocacy, defending fans’ interests in cases regarding copyright and fair use, and lobbying for more favorable laws.
Digital labor rights, like any labor rights, depend on workers’ ability to organize in pursuit of their interests. The idea of demanding pay for data depends on internet users coming together in something like a labor union or a craft guild, bargaining with data buyers and using strike threats to win contracts. Skilled translators or people with a specific medical condition might band together based on their knowledge of the value that their data could provide. Weyl suggested to me that users start with Wikipedia, since it has its own complicated, semi-democratic governance system.
“They should try to bargain,” he said. “And government should give them the power to bargain: ‘We’re going to stop you from using our content in some kind of way if you don’t offer some shared value to support our community.’” In the case of fan labor, Stanfill added, a union might be less interested in money than in shared credit and the right to remix commercial products in fan communities.
Recently, Instagram memers announced the formation of their own union, IG Meme Union 69-420, with actually-serious demands for better communication with the company, a more transparent appeals process for account bans, and protection from other users stealing and monetizing creators’ content.
Digital labor rights, like any labor rights, depend on workers’ ability to organize.
Users might also seek to collectively own their own data. Trebor Scholz, a culture and media scholar at The New School who writes about paid and unpaid digital labor, points to MIDATA, a Switzerland-based nonprofit cooperative that collects data on everything from blood tests to debit card usage, and then allows people to determine how their own information used. Members can actively choose to share selected parts of their data with others, like medical researchers. Scholz envisions extending that kind of model to other applications, like “smart cities,” where sensors and mobile apps gather data on traffic jams, water supply, and library needs. Big tech companies frequently propose organizing these kinds of projects, but are met by local communities with well-justified skepticism, since it’s easy to glean information on individuals from collections of supposedly anonymous data. Scholz suggests that a better plan would be a cooperatively run, locally governed organization that collaborates with companies like Google and Facebook to help collect information without letting them run the show.
“The cooperative could govern and own the raw data, essentially encrypt it,” Scholz said. “They can then pass on data models to those companies. That means that they are able to financialize the data, but not the raw data. They could never identify a person.”
Ultimately, any fight for digital workers’ rights depends partly on action by government, on the municipal to the national and international levels—to affirm rights to personal data, force companies to improve their terms of service, change copyright law, and grant labor protections for data creators. Some people despair at pitting government bureaucrats against rich, fast-moving tech giants. But Howard thinks we shouldn’t. “Government should not operate on the model that science is always going to outpace our ability to regulate it, that somehow science moves faster than law can,” she said. “But that is a very useful argument for science.” What is crucial—whether we’re Wikipedians, fan fiction writers, or just occasional Facebook users—is to push governments for better regulations and appeal directly to media companies to acknowledge the value we’re providing for them. And that means recognizing that we’re all digital laborers.
This article has been corrected to reflect that Mel Stanfill is a scholar at the University of Central Florida.
Editor: Betsy Morais
Fact-checker: Ethan Chiel