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When infrastructure is understood as an irrational social formation, emotional labor tends to compensate for a perceived lack of resources. Scholars who are used to the invisibility of traditional library services, for instance, find that digital projects expose hierarchies and bureaucracies that they don’t want to negotiate or even think about, and the DH librarian or one of her colleagues steps in to run interference. Why can’t the dean of libraries just tell that department to create the metadata for my project? After all, they already create metadata for the library’s systems. Why can’t web programming be a service you provide to me like interlibrary loan? I thought the library was here to support my scholarship. Why can’t you maintain my website after I retire–exactly the way it looks and feels today, plus update it as technology changes? In some conversations, these questions may be rhetorical; it may take emotional labor to answer them, but doing so exposes the workings of the library’s infrastructure–its social stack.

How does DH fit within this megastructure? According to some critics, DH is part of the problem of the neoliberal university because it privileges networked, collaborative scholarship over individual production. If creating a tool (hacking) or using computational methods has the same scholarly significance as writing a monograph, then individualized knowledge pursued for its own sake, the struggle at the heart of humanistic inquiry, is devalued. Yet writing a book always depended on invisible (gendered) labor in the academy. Word processing, library automation, and widespread digitization are just three examples of the support labor for traditional scholarly work that Bratton’s globalized technology Stack has absorbed. (And we know that the fruits of that labor are in no way distributed equitably.) What has changed in the neoliberal university is that the humanities scholar becomes one more node in a knowledge-producing system. Does it matter, then, whether DH work produces ideas or things, critics say, if all are absorbed into a totalizing system that elides the individual scholar’s privileged position? This is of course a vision of scholarship that is traditionally specific to the humanities; lab science and the performing arts, for example, have always been deeply collaborative (but with their own systems of privilege and credit).

Video games, like work, are basically a series of quests comprised of mundane and repetitive tasks: Receive an assignment, travel to a location, overcome some obstacles, perform some sort of search, pick up an item, and then deliver it in exchange for a reward—and, usually, another quest, which starts the cycle all over again. You are not playing the game so much as following its orders. The game is your boss; to succeed, you have to do what it says.

Instead of working, they are playing video games. About three quarters of the increase in leisure time among men since 2000 has gone to gaming. Total time spent on computers, including game consoles, has nearly doubled. You might think that this would be demoralizing. A life spent unemployed, living at home, without romantic prospects, playing digital time wasters does not sound particularly appealing on its face. Yet this group reports far higher levels of overall happiness than low-skilled young men from the turn of the 21st century. In contrast, self-reported happiness for older workers without college degrees fell during the same period. For low-skilled young women and men with college degrees, it stayed basically the same. A significant part of the difference comes down to what Hurst has called "innovations in leisure computer activities for young men." The problems come later. A young life spent playing video games can lead to a middle age without marketable skills or connections. "There is some evidence," Hurst pointed out, "that these young, lower-skilled men who are happy in their 20s become much less happy in their 30s or 40s." So are these guys just wasting their lives, frittering away their time on anti-social activities? Hurst describes his figures as "staggering" and "shocking"—a seismic shift in the relationship of young men to work. "Men in their 20s historically are a group with a strong attachment to the labor force," he writes. "The decline in employment rates for low-skilled men in their 20s was larger than it was for all other sex, age, and skill groups during this same time period." But there's another way to think about the change: as a shift in their relationship to unemployment. Research has consistently found that long-term unemployment is one of the most dispiriting things that can happen to a person. Happiness levels tank and never recover. One 2010 study by a group of German researchers suggests that it's worse, over time, for life satisfaction than even the death of a spouse. What video games appear to do is ease the psychic pain of joblessness—and to do it in a way that is, if not permanent, at least long-lasting. For low-skilled young men, what is the alternative to playing games? We might like to imagine that they would all become sociable and highly productive members of society, but that is not necessarily the case.

A military shooter might offer a simulation of being a crack special forces soldier. A racing game might simulate learning to handle a performance sports car. A sci-fi role-playing game might simulate becoming an effective leader of a massive space colonization effort. But what you're really doing is training yourself to effectively identify on-screen visual cues and twitch your thumb at the right moment. You're learning to handle a controller, not a gun or a race car. You're learning to manage a game's hidden stats system, not a space station. A game provides the sensation of mastery without the actual ability. "It's a simulation of being an expert," Wolpaw says. "It's a way to fulfill a fantasy." That fantasy, ultimately, is one of work, purpose, and social and professional success.

In my last year’s analysis of the MOOC space, I concluded that there’s been a decisive shift by MOOC providers to focus on “professional” learners who are taking these courses for career-related outcomes. At the recently concluded EMOOCs conference, the then CEO of Coursera, Rick Levin, shared his thoughts on this shift. He thinks that MOOCs may not have disrupted the education market, but they are disrupting the labor market. The real audience is not the traditional university student but what he calls the “lifelong career learner,” someone who might be well beyond their college years and takes these online courses with the goal of achieving professional and career growth.

One of the lessons I learned from running Class Central is that to make money, you need to make others money. By targeting professional learners, MOOC providers are trying to exactly do that. To better serve this audience, every MOOC provider has launched products that range from tens of dollars to tens of thousands of dollars. As a professional learner, I feel a certain amount of comfort knowing that high-quality educational material exists for skills that I would want to learn in the future. But if you are true lifelong learner—the ones that helped start all the hype in the first place—the MOOC experience has largely been reduced to basically a YouTube playlist with a cumbersome user interface. Unless, of course, you are willing to pay.

Unfortunately, the enemy is complacency. Tech workers trust their founders, find labor organizing distasteful, and are happy to leave larger ethical questions to management. A workplace free of 'politics' is just one of the many perks the tech industry offers its pampered employees. So our one chance to enact meaningful change is slipping away. Unless something happens to mobilize the tech workforce, or unless the advertising bubble finally bursts, we can expect the weird, topsy-turvy status quo of 2017 to solidify into the new reality. But even though we're likely to fail, all we can do is try. Good intentions are not going to make these structural problems go away. Talking about them is not going to fix them. We have to do something.

Can we fix it? Institutions can be destroyed quickly; they take a long time to build. A lot of what we call ‘disruption’ in the tech industry has just been killing flawed but established institutions, and mining them for parts. When we do this, we make a dangerous assumption about our ability to undo our own bad decisions, or the time span required to build institutions that match the needs of new realities. Right now, a small caste of programmers is in charge of the surveillance economy, and has broad latitude to change it. But this situation will not last for long. The kinds of black-box machine learning that have been so successful in the age of mass surveillance are going to become commoditized and will no longer require skilled artisans to deploy. Moreover, powerful people have noted and benefited from the special power of social media in the political arena. They will not sit by and let programmers dismantle useful tools for influence and social control. It doesn’t matter that the tech industry considers itself apolitical and rationalist. Powerful people did not get to be that way by voluntarily ceding power. The window of time in which the tech industry can still act is brief: while tech workers retain relatively high influence in their companies, and before powerful political interests have put down roots in the tech industry.