On Amazon’s Mechanical Turk job board, a recent posting simply read “enter missing data.” The task was described as “add and edit data from a pdf.” The pay: 25 cents. Amazon describes Mechanical Turk, a website that has been operational since 2005, as providing “an on-demand scalable, human workforce to complete jobs that humans can do better than computers.” Indeed, that is the purpose of many of the Human Intelligence Tasks (HITs) listed on the site: getting a human brain to figure out something that artificial intelligence is not able to do, yet.
A vast network of people inform the automatic smart technology that is changing our world by making everything easier, from Google image searches to identifying objectionable content. Somewhere along the line, a human had to tell the computers what’s what. Amazon’s Mechanical Turk is designed partly to find and fill that information void—the site’s tagline describes it as “artificial artificial intelligence.”
Writing in 2014 for the technology site Gizmodo, Eric Limer described working as an MTurker—the slang for the roughly half-million workers in 190 countries that Amazon says are available to complete HITs. “If you have a functional cerebral cortex, an internet connection, and a few minutes to spare, you can pick up a handful of odd jobs—the oddest of jobs—and make a few bucks, pennies, and nickels at a time,” Limer wrote. “It’s weird, fascinating, perplexing, and a little depressing, all at once.” Limer was describing one small employment niche in the mid-2010s, but he may as well have been speaking much more generally. The last decade has seen a transformation in not only the nature of work, but also in workers themselves, and thus in our communities and cities.
To speak to a young person today is to learn firsthand about the much-lamented “gig economy.” Work in the post-great recession era has come to mean, for this demographic, a personal schedule filled with a handful of jobs, temporary or contract positions, which together might equal a livable wage, subject to volatility throughout the year. Of those jobs, one might, in time, prove to be a permanent career. This is a reality of a job market that has tightened in the aftermath of an economic downturn, and remains largely occupied by an older generation working later into life than was previously considered normal. Freelancing is, for many, all there is—even with a status marker such as higher education. That “on-demand workforce” that Amazon brags it can summon via its Mechanical Turk site is much larger than the 500,000 potential fulfillers of HITs; it has become a significant part of the overall economy, particularly for its youngest cohort, millennials. Between October 2008 and 2009, the overall category of self-employed workers in Canada grew by 115,000; last year, another 60,000 became self-employed.
Australian sociologist Michael Scott situates a parallel cultural trend, the rise of hipsters, against this grim economic reality. In his paper. “ ‘Hipster capitalism’ in the age of austerity? Polanyi meets Bourdieu’s new petite bourgeoisie,” published earlier this year in Cultural Sociology, Scott argues that the new culture economy represented by this cohort—those “makers of bespoke perfume and beauty products, niche microbrewers, boutique tea blenders, producers of ethical hair products, vintners and sommeliers, tattoo artists, purveyors of recycled fashions and retro furnishings, independent vinyl record pressers,” and on and on—needs to be explored via the lens of production, not merely as a pattern of consumption or a social phenomenon. Whereas indulging in a specialty craft might, in decades past, have been seen as a rejection of, or at least deviation from, the mainstream, this kind of small-scale production has now become the mainstream. Indeed, it now reflects the reverse engineering of what used to be called corporate cooptation. Rather than high street fashion retailers stealing the markers of cool—in the dynamic that once made grunge a runway look, for example—today’s independent producers often aggressively pursue the possibility of selling out. “The Man” is a benevolent presence, a pathway out of economic precarity.
This freelance employment movement, bred by necessity, has in turn helped to deconstruct whatever barriers might have been left between the individual and the marketplace. Until the early 2000s a rejection, real or apparent, of the structures of consumerist society in some form or another remained a marker of cool. Now it is difficult to draw a line between the self and the system. In the era of the gig economy and the social-media personality, individuals are encouraged to monetize themselves, and the assets they leverage are not merely apartments or cars—skills, talents, hobbies, and sensibilities all become saleable products. And selling those would not be possible without the simultaneous rise of another new economic arena: the platform.
“At the most general level, platforms are digital infrastructures that enable two or more groups to interact. They therefore position themselves as intermediaries that bring together different users: customers, advertisers, service providers, producers, suppliers, and even physical objects,” Nick Srnicek writes in Platform Capitalism. “Rather than having to build a marketplace from the ground up, a platform provides the basic infrastructure to mediate between different groups.”
From that anodyne description, Srnicek builds an illuminating 120-page dissertation on where the platform came from, and where it might take us. He traces its rise in tandem with what he sees as a longer-term change in the economy, as far back as the 1970s when, he argues, there was a shift “away from secure employment and unwieldy industrial behemoths and towards flexible labour and lean business models.” There followed the 1990s dotcom boom and bust, during which ongoing trends such as massive venture capital investment in tech, increased outsourcing, and looser monetary policies took root. Still, the aftermath of the 2008 recession for Srnicek marks a turning point, as governments tightened their belts and key interest rates dropped to near zero. It was an important moment in the development of what is now an increasingly platform-driven economy, argues Srnicek, a digital economy lecturer at King’s College London. That’s because, with the resulting reduced rate of return on a wide range of financial assets, investors seeking higher yields had to turn to “increasingly risky assets—by investing in unprofitable and unproven tech companies, for instance.”
Among these risky ventures are the platforms that have now so entrenched themselves in life they are often used as verbs to describe the tasks they perform. Srnicek lumps them into five, occasionally overlapping, groupings: advertising (including Google and Facebook); cloud (Amazon Web Services, of which MTurk is a part, and Salesforce); industrial (GE and Siemens lease industrial equipment, as well as sell it outright, thus becoming providers as much as manufacturers); product (Spotify); and lean (Uber, Airbnb) platforms.
It is the first and last of that collection—the advertising and lean platforms—that are perhaps of most concern to the post–recession freelancer. Google, Facebook, Uber, Airbnb, and their smaller competitors and subsidiaries (anything from TaskRabbit to Instagram) are now key components in the gig economy. They either provide work directly or are the mechanism by which workers promote themselves, either to sell their wares or services or, in the case of social media, garner cash from brands using their accounts as advertising space (these are the so-called “influencers”).
Yet, as Srnicek suggests, the point of platforms is probably not really entrepreneurship. Behind the language of professional freedom and choice (“Work that puts you first. Drive when you want, make what you need,” Uber’s recruitment site declares) is all the information that is gathered about every transaction, interaction, or activity the platform enables, whether directly on its interface (usually an app), or outside it. And, as far as Srnicek is concerned, data ought to be considered as something much more than simply tabulated information stored on servers somewhere. Data, he writes, is “raw material that must be extracted, and the activities of users [are]…the natural source of this raw material.” Data extraction, he points out, “is becoming a key method of building a monopolistic platform.” The more data that a company can gather, and the more it can link it to other data it has or purchases elsewhere, the more refined its service becomes. At some point, the platform becomes so good at what it does that it not only outperforms the competition, but also effectively transforms from luxury into necessity. Uber, for instance, wants its cars to be so efficient that everyone stops using other modes of transport, be they public or private. The same goes for Facebook: when enough people organize their lives via the platform, so must everyone else, or risk social exclusion.
Defining data as a resource is a critical distinction for Srnicek, and its implications are potentially vast. First, it provides perspective to what we do online. We are not, for instance, surfing waves of information so much as we are the waves. It implies something more for those facing a dire economic present and questionable financial future. If data is the foundation for the platform economy, and we are all the providers of that data, then we are each in a certain way quite rich. The platforms need our activity and, as with Amazon’s Mechanical Turks, our brainpower—not only to gather data but also refine it and understand what it means. Does this make us—all the users who shop and read and play games and share our reflections online—labourers of a sort, creating a lucrative product? Srnicek considers this idea. “If our online interactions are free labour, then these companies must be a significant boon to capitalism overall—a whole new landscape of exploited labour has been opened up,” he writes. “If this is not free labour, then these firms are parasitical on other value-producing industries and global capitalism is in a more dire state.” Srnicek believes the latter to be more accurate.
At some point, we will not matter as much to that framework anyway. Once the deep learning has perfected its algorithmic pathways beyond a certain threshold, it is conceivable that humans will no longer be necessary to refine data on Amazon’s Mechanical Turk site or, in the case of Uber, act as nodes tracing the most efficient routes across a network of streets. A point will be crossed where human contribution becomes unnecessary, where we cannot make the platforms and the systems they have created any better.
Srnicek argues that before we reach that juncture, the platform economy will have either mostly collapsed, or become a pared-down version of its current state. Lean platforms like Uber or Airbnb may come under increased government regulation or more simple financial constraints, for instance. Since Srnicek’s book was released, this has indeed started to happen. Calls for regulating the major tech platforms—and even of trust-busting—have begun to gather momentum in Washington, D.C. in the wake of the 2016 U.S. presidential election, and the retrospective accounting of how misinformation spread online during the campaign. In the U.K., Uber and other lean service-oriented platforms have come under scrutiny for their failure to provide drivers and delivery people with things like holiday pay or a minimum wage. In 2018, data itself will be more closely regulated, at least in the European Union, which will require tech companies to collect explicit user consents before they use personal information, as well further enshrine the “right to be forgotten.” As the Financial Times reported in August, the sweeping changes could cost tech companies millions as they move to redesign products. For companies like Facebook, the cost—this time—is manageable. But more legislation will come, as will more ad blockers and regulation about ad transparency, and the challenges will mount for major platforms monetizing data. If advertising cash dries up entirely, an expanded internet of things—connected appliances and cars—might allow Google to turn “every good…into a service that charges by the use: cars, computers, doors, refrigerators, toilets.” Combined with continued stagnant wage growth, and rising inequality, Srnicek writes, “this future depicts a world with a massively increased digital divide.”
Along the way to that future—perhaps one in which everything is “uberized,” where work becomes ever more balkanized and the data created by that disruption further contributes to job losses, and so on—something may happen to us, individually, too. The expanding platform economy could continue to undermine labour laws, or change the traffic patterns of our cities, or the assumptions about the stability of our democracies—all of which would affect our lives. But, at a personal level, something stranger occurs. More of us, perhaps, begin selling the craft projects we make on the weekends on Etsy for extra money or renovate the basement to accommodate travelers via Airbnb. We, perhaps, also come to view our friendship networks as opportunities to market our social media accounts as ad space, rather than for old-fashioned human connection. Or, as we strap more Fitbits to our wrists to learn the data of our sleep cycles and steps to make our bodies better at both, we become not merely interested in the data we collect about ourselves, but driven by it, and invested in the idea that it can describe us better and define us better than simple language might.
In short, we will begin to regard our world, and all things in it, as either an opportunity for efficiency, or as an untapped financial resource—or both. In so doing, we will travel well beyond entrepreneurship, as we know it, or job freedom. This is something darker. On the way to shaping our economy to suit their own needs, the platforms will change us, too, making us more like them—to borrow a phrase, a kind of artificial artificial intelligence. Our lives will thus not merely be uberized in an exterior sense; we will come to think of ourselves and what we do as a system, an algorithm, a network. Each of us will become, more and more, a platform.