Media and New Capitalism in the Digital Age The Spirit of Networks

The term “crowdsourcing” is a play on the more familiar term “outsourcing.” The first article heralds “The Rise of Crowdsourcing” (Howe 2006), and the subtitle reads, “Remember outsourcing? Sending jobs to India and China is so 2003. The new pool of cheap labor: everyday people using their spare cycles to create content, solve problems, even do corporate R&D” (Howe 2006).

Thus, the article anchors the rationale of network production in the ability to tap into a “pool of cheap labor” and mobilize it for one’s production needs. This statement makes a distinction between outsourcing and crowdsourcing but at the same time uncovers how similar they are: in outsourcing, cheap labor is based on differentials in space; with crowdsourcing, cheap labor is based on differentials in time. The new source of cheap labor, this statement suggests, is predicated and conditioned on time that is deemed unproductive—“spare cycles” in the language of the article—that is, time that is not easily translatable to money and capital.

But what is the mechanism, or “trick,” by which productive forces, harnessed for the project of capital accumulation, can nevertheless be conceived as unproductive (as “spare cycles”) and hence be partially or wholly unpaid? Presumably the trick is technological—this is made possible by network technology. But the trick is also discursive: the trick is that this labor is construed in the digital discourse to be done by “everyday people,” rather than by professional, tenured, “in-house” workers. In other words, it is labor done by amateurs during their free time as an expression of personal interest and passion, not labor done by professionals as an expression of the more mundane attempt to make a living. No wonder that the teaser for the article on the front cover of Wired proclaims, “Crowdsourcing: A billion amateurs want your job” (Cover 2006, emphasis mine). The threat is clear: one’s position in the work force is threatened not so much by other workers but by a new class of workers: a new reserve army of (this time around) amateurs.

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Network technology is not only at the heart of a revolution in the mode of production but also at the heart of remapping the field of “socially necessary labor” in Marx’s terms (1990, 129), more specifially redrawing the lines between paid and unpaid labor. And to a large extent crowdsourcing, as a new discursive category of production, entails the transference of parts of the productive process from paid, organized, professional labor force to unpaid, atomized, amateurish enthusiasts. Underlying the digital discourse on crowdsourcing is the assumption that, because of network technology, more socially necessary labor can now be done without or with very little compensation: “The open source software movement proved that a network of passionate, geeky volunteers could write code just as well as the highly paid developers at Microsoft or Sun Micro systems. Wikipedia showed that the model could be used to create a sprawling and surprisingly comprehensive online encyclopedia. And companies like eBay and MySpace have built profitable businesses that couldn’t exist without the contributions of users” (Howe 2006).

An increasingly large chunk of the new economy, according to this source, is built—indeed conditioned—on labor that is not compensated or, as we will see below, involves new, more precarious, and partial modes of compensation. In Marxist terms, this is a case of superexploitation, where the whole value produced is in fact surplus value. And these new relations between capital and labor, according to the digital discourse, have been a trend ever since the introduction of network technology, with companies getting ever more sophisticated at extracting profit with minimal or no monetary return to workers: “All these companies grew up in the Internet age and were designed to take advantage of the networked world. But now the productive potential of millions of plugged-in enthusiasts is attracting the attention of old-line businesses, too. For the last decade or so, companies have been looking overseas, to India and China, for cheap labor. But now it doesn’t matter where the laborers are—they might be down the block, they might be in Indonesia—as long as they are connected to the network” (Howe 2006).

The network is seen in the digital discourse as a new repository for cheap labor, a mechanism for extracting hitherto unexploited resources. But looked at from the point of view of individuals, it is also a boon for small-scale producers: “Hobbyists, part-timers, and dabblers suddenly have a market for their efforts, as smart companies in industries as disparate as pharmaceuticals and television discover ways to tap the latent talent of the crowd. The labor isn’t always free, but it costs a lot less than paying traditional employees. It’s not outsourcing; it’s crowdsourcing” (Howe 2006). The final sentence highlights the fact that crowdsourcing is ultimately interpreted in the digital discourse as a new source of profitability. In that sense, crowdsourcing offers not a break but a continuation of the long history of capitalist exploitation, based on increasing levels of surplus value (rather than simply increased levels of productivity). Outsourcing and crowdsourcing are equated, since they are both manifestations of what network technology can offer in ever more sophisticated manners: cheap labor and increased exploitation. In the uncritical, even triumphant language of the digital discourse, this is not seen as exploitation at all because labor is done by “amateurs,” it is “latent,” and it is done outside of productive time.

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Network production entails a discursive redefinition of workers, with two key analytical innovations. The first is the dissociation of work (i.e., the investment of labor power in production) from employment (i.e., the institutional arrangement of livelihood, or the embeddedness of individuals within the social arrangement of production). The notion of “workers,” in fact, becomes an unstable signifier standing for hobbyists and dabblers. By extension, this redefinition also legitimates new modes of employment. This is of course not only an innovation but also a continuation of a long process of the rationalization and automation of production where labor and skills are increasingly objectified and are hence dissociated from the laborer (Aronowitz and DiFazio 1994; Braverman 1974; Robins and Webster 1999).

The second analytical innovation is the construction of workers as “prosumers,” an amalgam of producers and consumers. This renders the distinction between labor and capital obsolete and allows equating big corporations with small-time hobbyists; analytically, both are seen as homologous units of prosumption that can now meet in the digital marketplace and trade directly as equals. Moreover, with the redefinition of workers as prosumers, the category of “worker” as a distinct category is eliminated and instead the worker emerges as entrepreneur, an attribute I discussed in the previous chapter (Greenbaum 1995, 92; Huws 2003; Sennet 2006, 52).

It is through these analytical lenses that we can comprehend the astounding reference to the talent and work power of the crowd as “latent” (Howe 2006). According to this framework, only network technology is able to uncover and mobilize this talent and work power into productive results and, of course, with the condition that this talent is not paid or poorly paid. We must ask, then, why is it latent, and why can it only be uncovered and mobilized with network technology? Some answers can be glimpsed from some of the case studies of crowdsourcing explored in the article.

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TOPP_LING TH_E BASTION OF PROF_ESSIONA_LISM

The first story in Howe’s article is told from the point of view of a consumer, Claudia Menashe, who was looking to buy photographs for an exhibition she organized. She contacted Mark Harmel, a professional photographer who offered what is known in the industry as “stock photos” (i.e., existing images) for about \$150 each. Just before the deal was struck, Menashe stumbled upon iStockphoto.com, a stock photo Web site where she could find images for about \$1 each. How, the reporter asks, could this site “undercut Harmel by more than 99 percent? . . . By creating a marketplace for the work of amateur photographers, homemakers, students, engineers, [and] dancers” (Howe 2006). Notwithstanding the harsh consequences for Harmel, the professional photographer, this is an upbeat story about the democratizing nature of network production, where everyone can “make it,” since thanks to network technology, the bar for entering into the marketplace has been lowered like never before, and now “hobbyists, part-timers, and dabblers suddenly have a market for their efforts” (Howe 2006). This has completely transformed the business of photography: “Professional-grade cameras now cost less than \$1,000. With a computer and a copy of Photoshop, even entry-level enthusiasts can create photographs rivaling those of professionals like Harmel. Add the Internet and powerful search technology, and sharing these images with the world becomes simple” (Howe 2006).

And so, “the product Harmel offers is no longer scarce.” Network technology, according to the digital discourse, topples the bastion of what is by definition an exclusionary category: professionalism. It undercuts its guildlike privileges and instead empowers “the people” in two ways: hardware and software become cheap enough for nonprofessionals to acquire and a connection to the Internet renders virtually anyone a viable participant in the marketplace. “Technological advances in everything from product design software to digital video cameras are breaking down the cost barriers that once separated amateurs from professional” (Howe 2006); technology democratizes and popularizes economic opportunities. The boundaries between professionals and “enthusiasts” are blurred, since both have equal access to both the equipment and the social network needed to make and sell their products. Professionals and hobbyists are, of course, different in one crucial way: since the latter do not consider this activity their primary source of livelihood, they are ready to give away their products for free or very cheaply. These new circumstances create a market heaven: consumers are able to buy more cheaply, and amateurs are able to enter into the loop of production and creativity and offer the fruits of their passion. The only “loser” in this particular story about crowdsourcing seems to be Harmel, for whom photography is a profession and a career.

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If network production undercuts professionals in favor of the masses of producers and consumers, one expects not only individual photographers would be harmed economically from a crowdsourcing initiative like iStockphoto but other actors would be harmed as well, such as big commercial agencies of stock photography. The reality, however, proves otherwise. These companies have been adapting to the new realities of network production by various measures. For example, Getty Images, the largest stock photography agency in the world, overcame the threat of economic damage by purchasing iStockphoto for \$50 million in February 2006. Getty’s CEO explains the move: “If someone’s going to cannibalize your business, better it be one of your businesses” (Howe 2006).

Indeed, large companies, staples of the old capitalism, have been adapting to the new realities of network production by incorporating the new spirit of networks into their operating scheme. This, in turn, radically transforms the nature of production and indeed social relations as a whole. Another case study in the article focuses on the VH1 television channel hit show Web Junk 20, a compilation of videos shot by amateurs and posted on the Web. According to the article, this is not a solitary example; both network and cable television channels increasingly rely on crowdsourcing as a new mode of producing content on television. These channels include Bravo, USA Network, E!, and NBC. For example, more than 30 percent of Current TV’s programming consists of materials submitted by viewers (Howe 2006).

Here, a somewhat different facet of prosumption is revealed, as the practice is presented from the point of view of large media corporations, who are able to take advantage of the crowd. As the article points out, as prices for the professional video clips that VH1 had been using rose, Michael Hirschorn, an executive with the channel, realized he could use “the growth of video on the Internet . . . and build a show around it.” In a similar move to that made by Getty Images, Viacom—VH1’s parent company—bought iFilm.com, a Web archive of video clips and VH1’s main source for videos, for \$49 million.

The new productive model offers obvious financial gains: “The model’s most winning quality, as Hirschorn readily admits, is that it’s ‘incredibly cheap’—cheaper than almost anything else on television . . . Hirschorn thinks the crowd will be crucial component of TV 2.0. ‘I can imagine a time when all of our shows will have a user-generated component’” (Howe 2006).

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Notwithstanding the obvious economic sense of this scheme, the reporter nevertheless warily raises the question of whether “the crowd [can] produce enough content to support an array of shows over many years.” Hirschorn readily puts his trust in the network and the quality of the pool of free labor it musters. He predicts that “as user-generated TV matures, the users will become more proficient and the networks better at ferreting out the best of the best.” The article provides support for this optimism: a Pew survey found that 57 percent of twelve- to seventeen-year-olds online (twelve million individuals) are creating content and posting it on the Web. Moreover, in the case of iFilm.com, the crowd plays another important role in the process of television production: “Because iFilm already ranks videos by popularity, the service came with an infrastructure for separating the gold from the god-awful.” The crowd in this case serves also as an editorial board. In this model, “viewers serve as both talent pool and jury.” Hirschorn, therefore, predicts that “the model will succeed” (Howe 2006). In an ironic and historical turn of events, corporations such as VH1 are now vowing for a process of reskilling. They hope for “workers” to be more talented and skillful because crowdsourcing allows the company to meet them as producers in the marketplace, rather than as workers, and purchase strictly their products—that is, the end result of their labor—rather than their labor power and labor time. I will get back to that crucial point below.

The prime significance of crowdsourcing, according to the article, is not only economic. It is also not necessarily significant in terms of the cultural quality of the end products; most of these videos, the article admits, are vulgar and “stupid.” What’s important is the moral significance of crowdsourcing. The article suggests that crowdsourcing brings about a “new, democratic age of entertainment by the masses, for the masses” (Howe 2006). This populist ethos is also embedded in the names of many of the Web sites that thrive on network production. The formula “i + [content type]” (e.g., iStockphoto, iFilm) speaks to the empowerment of the “I”—the individual, amateur, unprofessional, “the people,” the masses—who can nevertheless shoot his or her own film and distribute it over the Internet. The same goes for the name of the video-sharing site YouTube, where the second person “You” refers to each individual user, or the social networking site MySpace, which again speaks of a personal space. The irony in this kind of allusion to the individual and “the people” is that many of these Web sites—which originally emerged as grassroots operations—are now owned by huge media corporations: Getty, Viacom, Google, and NewsCorp.

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CROWDS AND ENTHUSIASTS

Network production allows for a significant reduction in production costs by creating a business model based on the labor power of uncompensated and undercompensated laborers. But more than that, network production seems to be dependent on a new social compact, where “the people” receive more opportunities to engage their skills, creativity, hobbies, and passions and corporations receive hitherto unexploited sources for capital accumulation. On the other side of the coin, “the people” give up stable compensation schemes embedded in institutionalized employment and corporations surrender their claims for authority, professionalism, and control over content. The full scope and significance of this new social compact is unraveled in another case study of crowdsourcing, which goes to the heart of the new capitalism: the use of network production for research and development (R&D).

Network production can not only help mobilize the crowd in general but also separate the wheat from the chaff and get the best out of the crowd of highly skilled and professional individuals. “Not everyone in the crowd wants to make silly videos,” posits the article. “Some have the kind of scientific talent and expertise that corporate America is now finding a way to tap” (Howe 2006). The underlying assumption in this statement, and indeed throughout the story, is that the old way of tapping into people’s talent and labor power—by employing them—fell out of favor and that network production offers new ways to do it; indeed, network technology facilitates new relations of production.

The story focuses on one such professional—a retired physicist named Ed Melcarek—and one such mechanism for tapping into talent—the Inno-Centive Web site. Companies, the article says, are restructuring their R&D departments in accordance with crowdsourcing: “Forward-thinking companies are changing the face of R&D. Exit the white lab coats; enter Melcarek—one of over 90,000 ‘solvers’ who make up the network of scientists on InnoCentive, the research world’s version of iStockphoto” (Howe 2006).

The shift is from a standing army of scientists—tenured, employed full-time, and receiving benefits—to a reserve army in the form of a networked crowd. The reference to the “white lab coats” is telling: a staple, perhaps, of scientists’ habitus (like a physician’s stethoscope or a professor’s book under the armpit—a tool that is at the same time a professional signifier) but also an allusion (or a connotation, in Barthes’s terms) to a much deeper set of meanings. A white lab coat is the “uniform” of the worker; it stands for tenure, for being an integral part of a greater system—a peon perhaps, but a member nonetheless, without which the structure will not survive. The white coat—like the white collar and blue collar—is the emblem of the bureaucratic organization of industrial society par excellence. The figurative “exit the white lab coats” is therefore literal as well: exit tenure, mass employment, working class, collective bargaining, and so forth.

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In contrast to the previous examples of iStockphoto and iFilm, where big media corporations have colonized grassroots initiatives after the fact, in the case of InnoCentive the initiative originates at the center of power: “Pharmaceutical maker Eli Lilly funded InnoCentive’s launch in 2001 as a way to connect with brainpower outside the company—people who could help develop drugs and speed them to market. From the outset, Inno-Centive threw open the doors to other firms eager to access the network’s trove of ad hoc experts” (Howe 2006; emphasis mine).

These are not small-scale “start-ups” or not-for-profit initiatives, but well-established, rich, profitable companies. In addition to Eli Lilly, companies using InnoCentive include Boeing, DuPont, and Procter & Gamble.⁴ As the article puts it, these ad hoc experts “attack problems that have stumped some of the best corporate scientists at Fortune 100 companies” (Howe 2006). These companies “post their most ornery scientific problems on InnoCentive’s Web site; anyone on InnoCentive’s network can take a shot at cracking them.” The obvious reason why companies now “turn to the crowd [is] to help curb the rising cost of corporate research” (Howe 2006); companies offer merely \$10,000 to \$100,000 per solution.

But the economic benefit is only half the story, according to the article. The advantage that these companies see in crowdsourcing is the ability to mobilize the collective intelligence, or “smartness,” of the Web—smartness that does not exist anywhere else—to solve complex R&D problems. In fact, even though not all individuals in the crowd of solvers are experts and professionals (“the solvers are not who you might expect. Many are hobbyists . . .”), collectively, the article argues, the intelligence of the network is superior: “The strength of a network like InnoCentive’s is exactly the diversity of intellectual background” (Howe 2006).

Network production brings with it new modes of employment that are more flexible and precarious. And the digital discourse offers an explanation of them based on the inherent superiority of the network as a mechanism for the mobilization of dispersed skills. Hence, the legitimation for these new types of ad hoc employment schemes is based not only on economic reasoning (that this type of employment costs less and is more flexible and less burdening from the point of view of employers), and not only on emancipatory reasoning (that it allows more flexibility from the point of view of employees who would rather not be locked in committed—but possibly unsatisfying and stultifying—working relations; more on that below), but also on a new network reasoning, according to which the network is a repository of superior intelligence. Through the network, companies are able to tap into the expertise and knowledge of many more individuals than they can ever employ directly, and in turn, they can achieve better, smarter results (materialized in the form of products). Recall Kelly’s assertion that “no one is as smart as everyone” (Kelly 1998, 14). This is also very much in line with Friedrich Hayek’s conception of market information as tacit and dispersed (discussed in Chapter 3), but in this case the formula is applied not simply to information about markets but to information in the sense of specialized, professional, academic, and practical knowledge and expertise.

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Network production is presented as the condition for two trends, which are conceived as intertwined and codependent. On the one hand is the universal benevolence of a new superior smartness, which can lead—who knows?—to the development of a new life-saving drug by Eli Lilly. On the other hand is the new labor regime of loose, ad hoc, flexible employerworker relations epitomized by such projects as InnoCentive. These two trends are constructed as intertwined; that is, in order to reap the benefits of this new network rationality we must accept the more flexible, precarious, and privatized regime of employment, since both are predicated on the characteristics of the network. Network technology has the ability to make production more rational, but to do that successfully, it is implied, workers must be redefined as autonomous nodes in the network that can be flexibly mobilized to a specific project and then let go (see Figure 5.1).

To be more precise, according to the digital discourse, to achieve superior smartness we must accept flexible employment, since both are predicated on the characteristics of the network, especially on “the strength of weak ties,” identified in the article as “a central tenet of network theory” (Howe 2006). Here, the notion of “weak ties” that the article borrows from sociologist Mark Granovetter is translated quite literally and unproblematically into the realm of production relations to mean weak ties between employers and employees, or between different nodes engaged in a collaborative project, as the digital discourse would have it.⁵

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The linking of network technology to both a new labor regime and superior smartness is given a concrete example in the article. Melcarek, the aforementioned protagonist physicist, is reported to have solved a problem posted by Colgate-Palmolive, earning \$25,000.⁶ The article reckons that “paying Colgate-Palmolive’s R&D staff to produce the same solution could have cost several times that amount—if they even solved it at all” (Howe 2006). But again, the story is not simply about costs. The reason why Melcarek could come up with the solution, which he admits “was really a very simple solution,” while the R&D department at Colgate-Palmolive could not is explained in terms of the structural limitations of the traditional R&D: bureaucratic, hierarchized, stiff, and rigid. While at Colgate-Palmolive’s R&D the task of solving a toothpaste tube–related problem was assigned to “test tube guys,” the solution Melcarek came up with required “training in physics” (Howe 2006), which he possessed. In other words, for Colgate-Palmolive, crowdsourcing was a matter not just of reducing costs of development but of being able to come up with a smarter solution by tapping into skills and talent they did not have and that in fact they did not know they needed.

Here, too, crowdsourcing is presented as rational and advantageous not only from the point of view of companies and the system as a whole but from that of individuals as well. Melcarek’s arrival at the position of a “solver”—as the crowd is referred to on the InnoCentive Web site⁷—is described as the happy culmination of a bumpy professional road. His studies in physics were followed by “a succession of ‘unsatisfactory’ engineering jobs . . . none of which fully exploited Melcarek’s scientific training or his need to tinker”; after all, the article concludes, “not every quick and curious intellect can land a plum research post at a university or privately funded lab” (Howe 2006).

This mismatch between Melcarek’s talent and a work position, in the traditional sense of the term, was accompanied by his reluctance to work in “a 9-to-5 environment.” Crowdsourcing is presented as a solution to the limitations put forth by the traditional job market, which consists of positions (which are located at definite and stable points in space and time) that are part of a career path. These are seen as close-ended and restrictive, in contrast to the open-ended and flexible character of employment afforded by network production, which is specifically adept at exploiting the full potentiality of individuals. From the point of view of his personal work life “for Melcarek, InnoCentive has been a ticket out of this scientific backwater” (Howe 2006). Melcarek’s work life is more free and liberated in another sense as well. His work takes place within a physical and temporal environment of leisure. Melcarek’s lab is described as a “‘weekend crash pad,’ a one-bedroom apartment littered with amplifiers, a guitar, electric transducers, two desktop computers, a trumpet, half of a pontoon boat, and enough electric gizmos to stock a RadioShack,” and he is doing his work there “on most Saturdays.”⁸ Having the temporal and spatial freedom that Melcarek enjoys and at the same time taking part in the loop of production is made infinitesimally easier, according to the digital discourse, with network production.

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