In 1968 a Norwegian science fiction writer named Tor Åge Bringsværd published a peculiar short story called “Codemus.” The story has achieved the kind of retrospectively prophetic quality that makes sci-fi such a useful imaginative map for navigating our relationship with technology. (It also happens to be a good story, clever and light on its feet in its portrayal of a looming techno-fascism.) Bringsværd’s tale is about a thirty-eight-year-old man named Codemus who lives in a thoroughly automated society. “In the efficient society everything goes as planned,” goes one of the story’s mantras. “In the efficient society everything goes the way it should.”

“Codemus” is set sometime in the fifth decade of the twenty-first century, and its manically efficient society displays the kind of sterilized exactitude that we might associate with sci-fi’s New Wave period, when writers were less focused on space travel and ray guns than on questions of politics and personal freedom. A worldwide computer network, much like the Internet, provides information freely, although people have access only to end-user terminals (here Bringsværd seems to have envisioned a version of the cloud). Everyone has been equipped with a “little brother”—a digital assistant that we might recognize as a smartphone, right down to its sinister double-duty as a tracking device. Little brothers wake their owners up, tell them when to go to work, guide them on their commutes, and bring them home. They are at once companions, fonts of information, communication tools (everyone talks on them while walking in public), and draconian taskmasters hiding behind the scrim of technological sophistication and awesome computing power. To disobey one’s little brother is to violate a central directive of this efficient society.

Codemus always follows his little brother’s commands, but one day, the gadget decides to rebel. Little Brother (Codemus refers to his affectionately, affording him the dignity of capital letters) fails to wake up Codemus for work. Little Brother later decides to take Codemus, who is still under the spell of his machine, out to the park. Not much happens; they bask in the sun and try to start up a conversation with a park employee, who is immediately spooked. This mild encounter represents a grave offense on a day when park visits aren’t scheduled. Soon Codemus is a fugitive, pursued by police and bloodhounds through the city’s monorail system. Shadowed by the authorities at every stop, Little Brother demands that Codemus leave him behind. “They’ve got a fix on me, naturally,” Little Brother says, presaging an era when communication and surveillance would become synchronized processes. “I’m leaving a regular wake of radio waves behind us.”

Codemus doesn’t want to abandon his gadget-cum-companion, but eventually he acquiesces and dumps Little Brother. Soon fear, confusion, and emptiness take hold. Codemus has no idea who he is or what he’s supposed to do. “A human is a social entity,” goes another of the story’s aphoristic mantras, and Codemus is now alone. He is utterly, metaphysically lost. He decides to give himself up and falls into the arms of his pursuers. The story ends with Codemus “led back to the flock,” given a new little brother, and returned to the cool embrace of the efficient society. His purpose, such as it is, is restored.

We may not live in the dystopian society forecast by Bringsværd, but many of its elements are recognizable in ours. The smartphone has become the universal prosthetic. Its widespread adoption has helped create a surveillance climate in which everyone is his own little brother and everyone may be tracked at all times. Indeed, Codemus’s world resembles nothing so much as the handiwork of the visionary engineers at Google. There’s the same trademark ethos of all-consuming paternalism, the same seamless use of cloud computing and data collection as a bastion of social order, the same embrace of efficiency as a supreme value. There’s even the same promotion of automated transport free of human interference. Little Brother is like a hopped-up version of Google Now, the search giant’s personal assistant that spends all day rifling through your data, reminding you when you have meetings, when you should leave for your next appointment, how you should get there, what news might interest you, and so on ad infinitum.

Let’s step back for a moment—or rather, float upward a bit, and imagine a bird’s-eye view of this society, one in which harried workers are sent to and fro by way of commands conveyed to them through personal computing devices. They don’t know why they are doing these things, nor what sort of calculus informs all their data-charged activity. But still they follow the commands, which come with the computer’s imprimatur of mathematical precision and authority. They move between tasks with all the attention and care of worker bees; accomplishing the job without hesitation is all that matters. They live and work in conditions of closely choreographed banality.

From this vantage, the efficient society that terrorizes and comforts Codemus, and enfolds him in the straitjacket of a diffused, technologized fascism, resembles the experience of many workers today. Increasing numbers of people receive their instructions from, and report back to, software and smartphones. Whether operating a bin selector in an Amazon warehouse or freelancing from a coffee shop, many Americans work long days without having contact with other human beings—neither coworkers nor supervisors. (There are no subordinates for this class of workers.) Everything they do is tracked, because efficiency is the sine qua non. Some of them work for online labor markets like Elance, oDesk, and Amazon’s Mechanical Turk, which offer micro-jobs that can be done remotely, with little to no training. They complete surveys, tag photos, and transcribe interviews, for pay of a few dollars per hour or at a piecework rate of little more than a few cents per task. Occasionally, a job requires someone to go out into the physical world to confirm that a restaurant is still open or to photograph a store display so that the multinational company paying for it knows that it (and thousands of other displays like it, scattered around the country or the world) is set up properly.

The greatest deception of crowdsourcing is the notion that there is a crowd at all.

These labor markets depend on a kind of internalized offshoring. By fine-tuning an increasingly unstable employment regime—part of a countrywide “jobless recovery”—companies can focus on retaining and fairly compensating highly skilled (and highly sought after) employees, such as engineers, lawyers, programmers, doctors, and scientists. Meanwhile, less complicated work can be either farmed out to low-wage freelance and temporary workers or subdivided into smaller and smaller units of work, which are then widely distributed through a cloud-based labor market. The result is an extreme form of Taylorism: in boom conditions, workers have more tiny tasks than they can say yes to, but they acquire no skills, they learn nothing about the product or service to which they are contributing, they have no contact with other workers, and they have no chance to advance or unionize. They simply do the task offered to them, for a very low fee, and move on as quickly as possible. Imagine a factory in which each employee wears blinders and can see only the thing in front of him on the conveyor belt. An algorithm acts as the overseer, and this boss doesn’t miss a thing. (If you work for Gigwalk, for example, and don’t respond to a message within thirty minutes, the app may lower your rating in its system, decreasing your chances of getting more work.)

The software facilitating this transaction acts as the ultimate mediator; the employee and the employer never have to deal with one another directly. Payment can be unreliable and is wholly contingent on the employer accepting the laborer’s product. If the former doesn’t like what he receives, he can simply reject it and not pay the worker for his time. Contract employees have no chance, in this setup, to appeal or to revise their work.

Silicon Valley calls this arrangement “crowdsourcing,” a label that’s been extended to include contests, online volunteerism, fundraising, and more. Crowdsourced work is supposed to be a new, more casual, and more liberating form of work, but it is anything but. When companies use the word “crowdsourcing”—a coinage that suggests voluntary democratic participation—they are performing a neat ideological inversion. The kind of tentative employment that we might have scoffed at a decade or two ago, in which individuals provide intellectual labor to a corporation for free or for sub-market wages, has been gussied up with the trappings of technological sophistication, populist appeal, and, in rare cases, the possibility of viral fame. But in reality, this labor regime is just another variation on the age-old practice of exploiting ordinary workers and restructuring industrial relations to benefit large corporations and owners of the platforms serving them. The lies and rhetorical obfuscations of crowdsourcing have helped tech companies devalue work, and a long-term, reasonably secure, decently paying job has increasingly become a MacGuffin—something we ardently chase after but will likely never capture, since it’s there only to distract us from the main action of the script.

Brother, Can You Spare a Cycle?

No bad big idea achieves its full cultural potential without first being sacralized by Wired magazine. Crowdsourcing is no different. In June 2006 the tech industry’s bible ran a story called “The Rise of Crowdsourcing” (the cover headline was more typically hyperbolic: “A Billion Amateurs Want Your Job”). “The new pool of cheap labor,” the article’s writer, Jeff Howe, explained, is “everyday people using their spare cycles to create content, solve problems, even do corporate R&D.”

The casual characterization of human beings as something like modular computer components, complete with their “spare cycles,” was a revealing tic, one that has gone on to mark much of the subsequent popular literature on crowdsourcing. In this field, humans are required only so long as they complete the minimum amount of work that cannot be done by software. Even if they are replacing highly paid and skilled human beings, they are still treated like vestigial parts of a machine. As a driver for UberX—a vast, imperious experiment in crowdsourcing amateur drivers to replace cabbies, with their thorny regulations and job security—told Re/code as part of a complaint about Uber’s company policies, “We have become the functional end of the app.”

And that’s the ugly, dystopian truth at the heart of the networked digital economy: crowdsourced workers are expected to work seamlessly with software, following its commands. Software has replaced corporate bureaucracy as the inscrutable taskmaster. It’s become practically a legal entity unto itself. Millions of dollars in potential tort awards now depend on if and how Uber drivers are interacting with the app when they get into traffic accidents, run over pedestrians, or assault passengers. In March Uber announced new limited insurance coverage for UberX drivers, but the company continues to downplay its liabilities. After all, it’s not even a transportation or taxi firm but a “transportation network company” or, as it’s also been referred to, a “peer-to-peer ride-sharing service.” Uber engineers just make the app; what happens to people using it is of little concern to them.

This combination of treating humans like machines and recasting work as something different—something casual, informal, and frivolously fun—is a perennial selling point for the digital world’s army of crowdsourcing consultants. At the same time, it’s an all-too-obvious horror show for anyone still clinging to any critical detachment from the booster-mad tech scene. “Distributed labor networks are using the Internet to exploit the spare processing power of millions of human brains,” Howe explained, as if people are just waiting for corporations to call up and ask if they have any extra neurons available. The corollary is that people shouldn’t expect much for donating these spare cycles, but corporations can profit tremendously.

What emerges from Howe’s article—which, perhaps inevitably, resulted in a book-length treatment, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business—is the sense that crowdsourcing is indeed a good way to extract labor from masses of people at very low cost. Whether that labor will be done ethically or produce good work are other matters. “Crowdsourcing sites are not communities from which good ideas and products spring,” scholar Daren C. Brabham wrote in a study of iStockphoto, the micropayment platform that decimated the market for many professional photographers by offering up user-submitted stock photography at bottom-of-the-barrel rates. This is likely true, but companies that turn to crowdsourcing benefit from high margins—TV shows that make use of clips submitted by viewers, from America’s Funniest Home Videos to more recent programs on VH1 and Comedy Central, are incredibly cheap to produce—and highly advantageous economies of scale. If thousands of people are submitting ideas to you for free, some of them are bound to be good, or at the very least useful. And it’s much cheaper to have a couple of interns sorting through submissions for T-shirt ideas than it is to pay professional artists to do the design.

That’s why corporate America has also used crowdsourcing for more rarified work. Take InnoCentive, a platform on which companies like Eli Lilly and DuPont post complex problems for the public to solve—how to improve art restoration, say, or to inject fluoride into toothpaste tubes. Winning solutions may earn tens of thousands of dollars in rewards—a hefty amount, sure, but pennies compared to what these companies usually spend on research and development. In the process, a few garage tinkerers might make off pretty well, while Boeing or Procter & Gamble can slash its R&D department and harvest ideas from people who will never be in a position to sue them for infringement of intellectual property rights or to go work for a competitor.

These benefits haven’t been lost on the Fortune 500, which has taken to crowdsourcing and similar efforts in the same way it has to social media. Both technological platforms allow companies to interact directly with customers and to offer the impression that they are something other than impersonal, profit-driven monoliths beholden only to their shareholders. By running contests soliciting ads for major media events, brands like Doritos and Dove can save on their advertising budgets while also earning good press for appearing to be open to contributions from the public. The winning entries then are cast as meritocratic victories of amateur creativity rather than low-cost replacements for the professional ad campaigns for which agencies (their questionable taste aside) charge millions.

One might, in jaundiced fashion, nonetheless regard the crowdsourced life as yet another flourish of self-inflicted market idolatry on the part of the digerati—if not a natural-selection mechanism for the guileless amateurs who would have rolled over in similar fashion if they’d been graced with a cubicle in a Silicon Valley coding farm. But that’s just the problem: crowdsourcing has burrowed its way into all realms of life, most notably into government, philanthropy, higher education, and other sectors from which one might, in more confident chapters in our political economy’s development, expect some countervailing force against the land rush for free labor and opportunistic pseudo-populism. Instead, throughout the public sector as well as in the corporatized sanctums of the market, workers are urged to collaborate in their own systematic casualization and deskilling, all in the name of libertarian emancipation.

Uber Alles

A confluence of conditions has allowed crowdsourcing to thrive: the advent of highly distributed, mobile computing; the steadily blurring distinctions between work and play; an efficiency fetish in which all possible work must be captured and put towards productive ends; and a sense that technology is inherently empowering and beneficent.

The field also couldn’t exist without a generalized sense that liberal institutions are either in disarray or not up to tackling twenty-first century problems. In the crowdsourcing world, these challenges are inevitably cast as confusing, complicated, and amenable to technological fixes that politics or social movements can’t provide. And yet every crowdsourced appeal on GoFundMe or GiveForward for someone’s medical care—whether an impoverished artist or a victim of a mass shooting—is itself an outrage. These appeals are much more than the online equivalent of a charity bake sale. Spontaneous and virtuous outbursts of public generosity, for all the genuine good they can achieve for individual petitioners, are nonetheless powerful indictments of the public’s myopia, for no one should ever have to start a fundraiser to afford medical care. We’re willing to click “donate” to give $20 to someone in a time of dramatized suffering—it makes us feel good; we can share our involvement on social media; we feel a genuine longing to help someone in need—but are unable to mount the kind of sustained campaign needed to procure healthcare for everyone. And with every heartwarming story of a crowdfunding goal achieved (complete with the platform taking its cut), the case for systemic reform suffers.[*]

From healthcare to defense, the call for the private sector to usurp the responsibilities of government always beckons. Take the example of the increasingly militarized United States–Mexico border. After pouring a billion dollars into SBInet, the so-called “virtual” border fence designed by Boeing, the Department of Homeland Security abandoned the project in 2011. Steve Smith, a member of the Arizona State Legislature, shepherded into law a bill to crowdfund the fence, along with a state-sanctioned website, buildtheborderfence.com. Three years later Smith’s project was dead, having raised only $264,000—far less than the federal government’s $2.8 million estimated price tag for one mile of fencing. Even with Smith’s plan to use convict labor, the $264k haul was not enough to do anything, and the funds, which were reportedly solicited from corporations and private citizens alike, remain stuck in a state account. The irony of this debacle is practically recursive: here was a failed campaign to make up for the failure of the government to build a fence that, even if it had worked, represented a solution to a nonproblem—that of dangerous illegals taking away American jobs and bringing drugs and terrorism in their wake.

An app’s terms of service agreement is the closest thing we have to an employment contract.

Yet the libertarian excitement for crowdsourcing endures, founded in the misguided belief that once power is arrogated away from doddering governmental institutions, it will somehow find itself in the hands of ordinary people. In one typical effusion of libertarian magical thinking, William D. Eggers, writing earlier this year in Reason, marveled over the casual poaching of work via the miracle of software. He began by praising Luis von Ahn, who has made a career out of crafting fiendishly inventive technologies that manage to extract labor out of web users without their knowledge. Von Ahn’s breakthrough project was reCAPTCHA, a version of the now-ubiquitous online tests used to verify that a person is not a spambot. This program, bought up by Google in 2009, shows two words, barely legible and contorted into loopy shapes, to a user, who types them in a box. When she types them correctly, she verifies that she’s a human being, but in the process, she also transcribes a word or two from Google’s massive book-scanning project—and she provides a service that the company’s optical character recognition software can’t. If one accepts the legitimacy of CAPTCHAs and similar verification schemes, then the harvesting of the user’s labor is incidental—which is precisely what makes it so ethically confounding.

Eggers also lauds another von Ahn invention: Duolingo, which, the writer explains, “allows people to learn a foreign language while simultaneously translating huge chunks of the Internet.” These pieces of the Internet—which fortunately remain (for now anyway) comparatively small—are mostly for-profit websites with which Duolingo partners. Companies like BuzzFeed and CNN submit articles to Duolingo, which duly parcels them out to its online battery of students, who work through them as translation exercises. A fully translated article is then aggregated from various students’ contributions, and voilà: a major media organization has a complete translation of its material, without the expense of hiring a professional translator or a local journalist to re-report the story.

One might counter that the students use Duolingo for free and that this is a way of repaying that debt. But most students participate in this arrangement unwittingly. What’s more, and far more troubling, Duolingo users are contributing to the erosion of the societal and market value of once-expert skills like translation. (They’re also translating for some pretty crummy media organizations.) One is left with a tough bargain: Do we accept Duolingo, for all of its subterfuges, as part of the inevitable drift of digitization within the working world—and as a lesser evil than, say, Google’s translation service, which has automated the process of translation and cut out human beings entirely?

Another option is to overlook these issues altogether, which is what Eggers chooses. He does say that “the genius of reCAPTCHA and Duolingo is that they divide labor into small increments, performed for free, often by people who are unaware of the project they’re helping to complete.” It’s disturbing that this arrangement excites him without reservation. Then again, that is the market worshipper’s creed: greater entanglement within the matrices of capitalist exchange is always, by sheer dogmatic definition, freedom. Thus, Eggers observes, ridesharing companies like Uber let us form “de facto taxi service[s]” and build “two-sided markets”—albeit ones in which, Eggers neglects to say, we are always buying and selling the basic components of our lives.

Unruffled, Eggers hops from glory to glory, next citing that other wellspring of techno-utopian pabulum: TED. In a TED Talk titled “Massive-Scale Online Collaboration,” von Ahn enthuses about “humanity’s large-scale achievements.” The most impressive of these, such as building the pyramids and the Panama Canal or landing on the moon, involved about one hundred thousand people. “The reason for that,” he says, is that “before the Internet, coordinating more than one hundred thousand people, let alone paying them, was essentially impossible.” Now, with the Internet, everything is different, because everything is always different with the Internet.

What von Ahn and his proxy, Eggers, neglect to note is that the pyramids were built with slave labor; that tens of thousands of workers died building the Panama Canal; that landing on the moon was one of this country’s shining achievements but also a specific product of a decades-long Cold War that gave birth to a military-industrial complex that continues to chew through our treasury and civil liberties alike. In the same register of uncritical and ahistorical gadget-enthrallment, they likewise fail to stipulate that the CAPTCHA-driven digitization of human knowledge they celebrate is merely a scaffolding on which Google can hang more ads (having begun the project without bothering to consult any of the authors or publishers who owned the original work).[**]

Workers are urged to collaborate in their own deskilling, all in the name of libertarian emancipation.

Small wonder, then, that the apostles of the crowdsourcing gospel casually annex the traditional functions of the public sector into their grand digital bargain. Despite their diehard libertarian animus against the public sector, they hew to the cartoonishly technocratic faith that government can wipe away most stubborn social complexities—provided that it does so with suitably robust measures of crowdsourcing. “Volunteers” will walk through Kenyan slums and use GPS units to tag landmarks. Finland’s national library is “perpetually short of funds”—it shouldn’t be, but no one bothers to consider that—so it will crowdsource volunteers to digitize documents. Health, online education, and work will be gamified and our data turned over to the owners of the platforms that will parse it for us, allowing us to live better. (These benevolent market actors surely won’t sell our precious data elsewhere—or if they do, they will at least once more fail to notify the originators of all this content that it’s been strategically repurposed.) Citizens will comment on laws directly, perhaps even writing them. We might sign up for a U.S. Patent Office trial program “in which each patent application runs past the eyes of several citizens, often with science backgrounds, rather than distracting a lone bureaucrat.” Often with science backgrounds, you say! And yes, a moment of thought for the lone bureaucrat, who is now, like the rest of us, an artisan creating folk art in his spare time; he too turns to crowdsourcing, but only when he needs to fill up the tip jar.

In this idealized type of digital exchange, the impermanence of these relationships, the ad hoc nature of it all, is a recipe for stability, not anxiety and disorder. Here there are no technological or economic divides. Everyone can afford the same gadgets and is able to put in time performing services, tracking personal data, and making suggestions that others—paid, professional, competent people—would have once made instead. The participants are diverse—contrary to academic studies showing that crowdsourcing projects tend to be white, male, and prosperous—and so the data is, too. Power accrues—though never to excess—to those with the right blend of moxie and good ideas. “The burden of basic services gets shifted from credentialed professionals to individuals empowered with technology,” Eggers says. Of course, in failing to exercise even the most basic critical faculties in this Pollyannaish account of the crowdsourced knowledge economy, Eggers is showcasing the colossal market failure of citizen journalism. A longtime consultant on government reform, he churns out online PR boilerplate that virtually doubles as an infomercial for the kind of services provided by his current employer, the neoliberal consultancy colossus Deloitte.

We Live as We Dream, Alone

The greatest deception of crowdsourcing is the notion that there is a crowd at all. Sure, there may be thousands of people participating in the T-shirt design contest, driving cars for Lyft, filling out paid surveys, or helping a police force identify looters in CCTV footage, but they are not assembled as a crowd. They are not in communication with one another, much less occupying one physical space. Each submission is handled individually, likely by a piece of software; as far as the system is concerned, each submitter is a data profile. There is no group of people organizing, conferring with one another, leveraging their power as a group, and finally submitting their work to someone else. This is a crowd only in name.

In Crowds and Power, his landmark study of crowds and the political and social forces surrounding them, Elias Canetti emphasizes that the crowd is a place of unification. There, distinctions are thrown off: “Only together can men free themselves from their burdens of distance; and this, precisely, is what happens in a crowd. During the discharge distinctions are thrown off and all feel equal.” This equality matters but is also “based on an illusion,” Canetti explains. Once the crowd disperses, its members return to their atomized lives as individuals in their own homes, with their own families and concerns; they don’t abandon these relationships for the sake of the crowd. But for at least a moment, they close that distance and unify for a common cause. Another word for this phenomenon might be politics.

The contemporary practice of crowdsourcing employs this illusion—that everyone is equal, united in a shared goal—while combining it with another popular deceit, that of meritocracy. Under the regime of crowdsourcing, everyone is actually competing with one another, ostensibly under protocols that are impartial and fair. But in reality, those contributing to a crowdsourced project control nothing about the terms of their participation. Sure, it may be up to them whether they want to participate at all, but under the clever labor-extracting end runs and subterfuges of many crowdsourced projects, contributors are commonly denied that most basic of democratic rights: consent of the governed (or in this case, the subcontracted). At its most manipulative, crowdsourcing produces projects along the lines of Twitch, an Android app that takes over your phone’s lock screen and, rather than having you enter an unlock code or pattern, asks you to answer a quick question or rate photos—microwork that benefits whichever patron may pay to place a task there. While apps like these aren’t yet the default, the next step is dismally clear—participation in crowdsourced work could soon be the condition of unlocking the devices we need to perform all our other crowdsourced tasks.

When they do have a choice, users don’t typically crowdsource their labor for the sheer giddy pleasure of selfless amateur participation. They tend, rather, to do it under false pretenses or simply because they have few other options for earning money or for gaining the attention of the sort of people who, they hope, might one day hire them for genuine wage labor.

In this way, crowdsourcing depoliticizes the crowd. It prevents crowd members from communicating with one another and from organizing. Those activities, after all, might upset whoever is running the design contest or controlling the transportation app that nominally employs them. Uber, for example, has responded to drivers protesting mass firings by claiming that these drivers received poor ratings through the app and that their accounts were merely “deactivated.” On Mechanical Turk forums, workers vociferously oppose unions, often claiming that MTurk work is individualistic and that a union would get between a worker and the person offering him a few cents or dollars to complete a menial task. (On the other hand, it’s rarely suggested in such forums that Mechanical Turk itself is getting between workers and those assigning tasks, or that workers might require some protections and would benefit from organizing.)

Constantly rated and assessed, these workers appear to have internalized the sense of competition imposed on them from above. They know that the communitarian rhetoric surrounding crowdsourcing is but a pretense and that fellow workers represent competitors for the few decently paying jobs available. And yet if crowdsourced laborers were able to come together and organize, they might find that their lot would improve in the long run. It is at the very moment that workers strike, as Canetti says, that their “fictitious equality . . . has suddenly become a real equality”:

As long as they were working they had very varied things to do, and everything they did was prescribed. But, when they stop work, they all do the same thing. . . . Stopping work makes the workers equals. Their concrete demands are actually of less importance than the effect of this moment.

In the harried, covertly competitive environment of crowdsourcing, this kind of stoppage seems impossible. There is no strength to be won from these weak ties. But it’s only through some kind of strike or organization that crowdsourced laborers could improve their working conditions. Unfortunately, the process by which that might be achieved is unclear. Whereas workers once hoped to unite to fight the edicts of management, crowdsourced workers would have to transcend algorithmic barriers and the dictates of software. How do you picket—much less launch a work stoppage—against a faceless app?

You can see where all this is going, pulled toward the death spiral of diminishing expectations. As governments continue to practice austerity, making lifetime employment and pension benefits a thing of the past, American corporations, despite a booming stock market and record cash reserves, follow suit. Stable employment, benefits, and retirement funds become anachronistic perks of a pre-digital workforce. Companies begin to think in terms of short-term spending rather than long-term investment, as borrowing and hiring both atrophy. More and more of us are forced to be contingent laborers, freelancers, crowdsourced volunteers, or “permalancers” always on the lookout for more opportunities, always advertising ourselves through social media and public networks, knowing—with a sense of generalized suspicion—that our public utterances on social media may influence our future job prospects. Risk assessment algorithms may already be parsing our social media profiles, pooling information to be used in a future background check. Obliged to work constantly to pay off household debt or school loans, we don’t have the time to learn the skills that would, we are told, allow us to succeed in the knowledge economy.

Large corporations, meanwhile, start to realize that they can not only build on existing outsourcing—which has seen human resources, IT, customer service, and a range of other support staff shunted overseas—but also practice a pro tem outsourcing at home, summoning pliable, cheap workers whenever they’re needed. Managers get plaudits for being technologically progressive and nimble—and of course, for cutting budgets in the process. Stock markets reward companies operating on high margins, so more employees are fired from already profitable companies. More power is granted to software engineers, executives, high-level managers, and those controlling the algorithms and the networks; these men (and they are mostly men) are plied with spectacular working conditions and stock options to keep them happy and supportive of the status quo.

Workers, in turn, have more mobility and a semblance of greater control over their working lives. But is any of it worth it when we can’t afford health insurance or don’t know how much the next gig might pay, or when it might come? When an app’s terms of service agreement is the closest thing we have to an employment contract? When work orders come through a smartphone and we know that if we don’t respond immediately, we might not get such an opportunity again? When we can’t even talk to another human being about the task at hand and we must work nonstop just to make minimum wage?

Here is where Tor Åge Bringsværd’s story deviates from reality. Yes, Codemus lived in a fully administered society where surveillance technology, automation, and the iron god of efficiency had coalesced into something irreproachable and frightening. But there was one aspect of his life that today seems too strange for fiction: he had a job that provided for all of his needs.

Would-be fundraisers must also submit to the onerous rules and service terms of crowdfunding platforms—and the pretense that these rules are the imperatives of an entirely impartial technology. GiveForward’s payment service, WePay, canceled a crowdfunding campaign for a severely ill woman who was a sex worker. Meanwhile, George Zimmerman raised hundreds of thousands of dollars via PayPal. When supporters of Darren Wilson raised half a million dollars on GoFundMe, the company issued a statement saying that it was “a neutral technology platform.” GoFundMe did find fault with one pro-Wilson appeal: “This campaign no longer meets GoFundMe’s stated requirement of having a valid Facebook account connected.”

It’s also worth noting that the TED series is itself a model of uncompensated digital labor; TED organizers rely on amateur contributors to translate and subtitle the breathless PR talks that conference organizers send caroming through the smartphones of the digerati. Hey, it worked for the pyramids!