Monday, December 5, 2011



Network Culture: Politics for the Information Age


Free Labour

Terranova defines free labour, here, as, “excessive activity that makes the Internet a thriving and hyperactive medium” (Terranova, 73). The social factory or society-factory is defined as, “work processes have shifted from the factory to society thereby setting in motion a truly complex machine” (Terranova, 74). Today, the Internet acts as this multifarious organism producing a network milieu. “Simultaneously voluntarily given and unwaged, enjoyed and exploited, free labor on the Net includes the activity of building websites, modifying software packages, reading and participating in mailing lists and building virtual spaces” (Terranova, 74).

Much criticism of Marx’s conception of labor persists in discourse today.
Donna Haraway identifies ‘informatics of domination’ as reflecting relationships between technology, labor and capital. Rejecting humanist positions, Gilroy, explains, “If labor is the humanizing activity that makes [white] man, then surely, this ‘humanising’ labor does not really belong in the age of the networked, posthuman intelligence” (Terranova, 74). Despite discussion, Terranova states that “the Internet does not automatically turn every user into an active producer and every worker into a creative subject” (Terranova 75).

Terranova defines the digital economy as a “specific mechanism of internal ‘capture’ of larger pools of social and cultural knowledge…. [and] an important area for experimentation with value and free cultural/affective labour” (Terranova, 76). With the digital economy came the New Economy. The New Economy marks “a historical period marker [that] acknowledges its conventional association with Internet companies, and the digital economy—a less transient phenomenon based on key features of digitized information” (Terranova 76).

Richard Barbrook posits that the digital economy is a mixed economy including a “public element, a market-driven element and a gift economy” (Terranova, 76).
Don Tapscott defines the digital economy as, ‘a new economy based on the networking of human intelligence.’ He furthers, “Human intelligence, however, also poses a problem: it cannot be managed in quite the same way as more traditional types of labour” (Terranova, 78).

Resistance pursues due to the unquantifiable nature of ‘knowledge.’ Terranova refers to the Internet as a “consensus-creating machine, which socializes mass of proliferated knowledge workers into the economy of continuous innovation” (Terranova, 81). The knowledge worker remains confined to class formations and are not necessarily given elite status despite their contribution to capital. However, it remains unclear why some individuals qualify as knowledge workers while others do not.

Italian autonomist, Maurizio Lazzarato describes immaterial labour as referencing two distinct realms of labor. First immaterial labour refers to the informational content within the commodity. In this sense, labour is seen through direct action where skills typically involve cybernetics and computer control. (Terranova, 82). Second, Lazzarato identified immaterial labour as that which produces cultural, rather than informational, content. This type of labour is not work in its typical sense but may represent a range of activities that aide in fixing popular cultural preferences. (Terranova, 82). According to Lazzarato all citizens have a change to contribute immaterial labour as it is not fixed by class. “This means labour is a virtually (an undermined capacity) which belongs to the post industrial productive subjectivity as a whole” (Terranova, 83). Therefore, postmodern governments encourage the potentialities of work to the unemployed.

Terranova notes that the unemployed, “must undergo continuous training in order to be both monitored and kept alive as some kind of postindustrial reserve force” (Terranova, 83). The postmodern agenda, however, did not happen overnight. Lazzarato states, “The virtuality of this capacity is neither empty nor ahistoric; it is rather an opening and a potentiality, that have as their historical origins and antecedents the ‘struggle against work’…and in more recent times, the process of socialization, educational formation and cultural self-valorization” (Terranova, 83). This agenda represents capitalist motivations of optimizing its citizens within the labor force.

Levy asserts that networks “enable the emergence of a collective intelligence” (Terranova, 85). We no longer think according to the Cartesian model of thought based on singularity (I think), but to a collectivity of thought (We think). Levy defines collective intelligence as “a form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills” (Terranova, 85). This proposes a flexible and constantly changing epistemology. Levy continues explaining the means and the ends to collective intelligence. “The basis and goal of collectivize intelligence is the mutual recognition and enrichment of individuals rather than the cult of fetishized or hypostatized communities” (Terranova, 85). Computers, particularly accentuate the inherent value of human intelligence as man’s productivity reveals hidden creative potentials.

In Karl Marx’s, Fragment on Machines, knowledge becomes’ incarnate in the automatic system of machines’ where labor is only a link within a mechanical organism. However, Terranova points out that the Italian autonomists ‘eschew the modernist imagery of the general intellect as a hellish machine.’ (Terranova, 87). Instead they find general intellect to be a principal productive force which was manifesting before them. No longer was the intellect a hellish machine but rather an ensemble of knowledge…which constitute the epicenter of social production.

Humanists believe that the Italian autonomists neglected the idea of mass intellectuality of living labor as it articulates general intellect. Precisely, mass intellectuality is, “ an ensemble, as a social body—is the repository of the indivisible knowledges of living subjects and of their linguistic cooperation…an important part of knowledge cannot be deposited in machines, but…it must come in to being as the direct interaction of the labor force’ (Terranova,87-88).

Neither knowledge labor nor unemployment acts as collective knowledge.
Knowledge labor is inherently collective; it is always the result of a collective and social production of knowledge. Capital’s problem is how to extract as much value as possible. Terranova notes both continuity and a break exists between, older media and new media as they relate to cultural and affective labor.

Continuity assumes the “common reliance on their public/ users as productive subjects” (Terranova, 88). However a split exists between the mode of production and in how power/knowledge acts in the two forms. The internet is highly decentralized and dispersed compared to television. Although old media also tapped into free labour, television and print media did so in a more structured way than seen in new media.Commercialization of the Internet is attributed as one of the key reasons for Barbrook’s gift economy. That is, increasing privatization and e-commerce create an economy of exchange.

The capitalistic logic of production becomes accelerated by ‘immaterial’ products
Humanistic concerns remain as the real seems to disappear as the Internet grew. Specifically, hyperreality represents the humanist nightmare. Hyperreality is, “a society without humanity, the culmination of a progressive taking over the realm to representation.” (Terranova, 90).While the commodity seems to disappear, it does so not in the material sense but the quality of labor put into the commodity a subsidiary. Commodities become ephemeral works in progress. That is, no finished product likely exists but only those that are indefinitely in the process of becoming. Therefore, the quality of the commodity depends on the quality of the labor.

Sustainability of the Internet is intrinsically dependent on massive amounts of labor. The Internet then, is sustainable only so far as it is: ephemeral, updatable and possesses a mass collective labor. “The notion of users’ labour maintains an ideological and material centrality which runs consistently throughout the turbulent succession of internet fads” (Terranova, 91).

Open-source movement demonstrates the overreliance of the digital economy as such on free labour, both in the sense of ‘not financially rewarded and of ‘willingly given.' (Terranova, 93).Terranova asserts that digital work is “not created outside capital then reappropiated by capital, but are the results of a complex history where the relation between labour and capital is mutually constitutive, entangled and crucially forged during the crisis of Fordism” (Terranova, 94). “Free labour is a desire of labour immanent to late capitalism and late capitalism is the field which both sustains free labour and exhausts it” (Terranova, 94). Therefore, the Internet acts as both a gift economy and advanced capitalist society

Here, Terranova explores what is known as the ‘Old web v. New web’ debate. Television shows, which are increasingly becoming ‘people shows’ or ‘reality television’ rely primarily on the audience just as the Internet relies on user activity. Terranova notes that these programs, “manage the impossible, create monetary value out of the most reluctant members of the postmodern cultural economy: those who do not produce marketable style, who are not qualified enough to enter the fast world of the knowledge economy, are converted into monetary value through their capacity to affectively perform their misery” (Terranova, 95).

“The digital economy cares only tangentially about morality. What is really cares about is an abundance of production, an immediate interface with cultural and technical labour whose result is a diffuse, non-dialectical antagonism and a crisis in the capitalist modes of valorization as such"
(Terranova,96).

The Internet channels and adjudicates responsibilities, duties and rights. Open and distributed modes of production represent, “the field of experimentation of new strategies of organization that starts from the open potentiality of the many in order to develop new sets of constraints able to modulate appropriately the relation between value and surplus value” (Terranova, 96) Therefore, productivity is critical as it creates value for capitalism. Terranova refers to this relation of value and surplus value as the ‘entanglement of emergence and control’ (Terranova, 97).


Soft Control

Terranova defines biological computing as, “a cluster of subdisciplines within computer science—such as, artificial life, mobotics and neural networks” (Terranova, 99). Biological computing is essentially a bottom up organization through the stimulation of, ‘the conditions of their emergence in an artificial medium—the digital computer.” (Terranova, 99).

Lewis Mumford, writing in 1934, argued against the prevailing industrial technological ontology, hoping it would be replaced by a new technological age. Mumford viewed this transition as a return to the organic. “Human technicity does not so much construct increasingly elaborate extension of man but rather intensifies at specific points its engagement with different levels of the organization of nature” (Terranova,98). However, the artificial played a key role in Mumford’s predictive analysis. While nature materializes out of these interactions, the relationship is also artificial, that is, it is both inventive and productive. The network becomes a topological production machine if understood as a ‘spatial diagram’ for the age of computing.

Once biological computing possesses the ability to outperform the programmer and his instructions emergent phenomena arises. That is, because biological computing possesses no material center, leaderless numbers of elements that are only bound by their own protocols, therefore making the Internet an explicit instance and product. The self-organizing nature of the network represents a mode of production illustrated by an excess of value. Abstract machines of soft control surface acting as a, “diagram of power that takes as its operational field the productive capacities of the hyperconnected many.” (Terranova, 99). reconceptualization of life occurred as a biological turn in computing arose, focusing on natural and artificial bottom-up organization.

Artificial life theorists, Charles Taylor and David Jefferson support this form of organization. “The living organism is no longer mainly one single and complicated biochemical machine, but is now essentially the aggregate result of the interaction of a large population of relatively simple machines. These populations of interacting simple machines are working at all levels of the biophysical organization of matter” (Terranova, 101). Terranova summarizes the consequences of the aggregation of the simple as it organizes matter. “As a consequence, ‘to animate machines….is not to ‘bring’ life to a machine; rather it is to organize a population of machines in such a way that their interactive dynamics is ‘alive’” (Terranova, 101).

Artificial intelligence now seeks to study the activity of neural cells in the central nervous system (CNS). Artificial life theorists seek to reproduce the mind’s complex features such as being able to hold an indefinite memory. Gregory Bateson explains the current scientific conceptualization of the brain. (Terranova, 102)

“We may say that the mind is imminent in those circuits of the brain that are completely within the brain. Or that mind is immanent in circuits which are complete within the system brain plus body. Or finally, that mind is immanent in the larger system—man plus environment.” (Terranova,102).

Biological computation must concern itself with the power of the minute, that is, theorists’ measure biological computation as it is exterior and relational in nature. No finite determination or central control is possible due to the multitude of variables; therefore, systems are eternally dynamic. The ‘open system’ does not die or reproduce in a self-creational sense but “they are always becoming something else” (Terranova, 102). These systems are therefore highly unpredictable and are thereby difficult to control. The lack of centrism in an open system also disallows the dissection of the creature because, “once the connection and mutual affection with other elements is removed, the individual element becomes passive and inert” (Terranova, 104). Therefore, despite mass collection of data regarding individuals, the true dynamic of the network proves unattainable. However, despite uncertainty regarding control, these open systems do provide the potential of enormous productivity generated by the collective nature of the open systems within the network.
“More is different”

Fluidity is a critical concept in New Economy capitalism as fluidity relates bottom up organizations and speed. Moreness is “explicitly linked to the need for a different immanent logic of organization that demands new strategies of control to take advantage of its potentially infinite productivity while controlling its catastrophic potential” (Terranova, 106). Maintaining such dynamic fluid environments requires the identification of a certain ‘phase space,’ recognizable at a certain level of speed.
John von Neumann linked evolutionary biology and computation when he devised a computational experiment named, cellular automata (CAs). CAs represented a “relatively new field that appeared in the midst of the intellectual dust that accompanied the development of the first digital computers” (Terranova, 109).

“CAs form dynamic milieus, space-time blocks, that have no real territorial qualities but do have rich topographies and challenging dynamics” (Terranova, 112). This occurs not because no central control exists, but because these cells are capable of spontaneous self-regulation.

Researcher, Stephen Wolfram, empirically classified CA dynamics using one-hundred runs of ‘the game of life.’ He subsequently catalogued four classes in which CAs fit. Class I CAs are those programs, which reached their computational limit or end point. Class II CAs, however, represent ‘limit cycles’ through self-replication of structures that glide across the ‘computational space’ by self-replication. Class III CAs produce fractured structures capable of self-replication like Class II CAs, but also possess the capability to scale and therefore progressively structure the CA. Finally, Class IV systems are highly chaotic, unstable and random. The random nature of this class results in no predictable time limits which make Class IV CAs highly unpredictable. Chris Langton subsequently reproduced Wolfram’s study but ran repeated runs of Ca systems thousands of time. As a result, Langton produced a new classification order but also a critical metric of measurement (the lambda). Lambda measures “the fluctuation of different CA systems with their relation to their computational abilities” (Terranova, 114). The lambda ranged from zero to one representing the most random systems incapable of computation (0) and the highly structured CA system also incapable of computation due to its inflexibility. Langton found that the key area of computation is identified with a border zone fluctuating between highly ordered and highly random CAs” (Terranova, 114).

Terranova first notes that fact that the CA run is ‘out of control,’ this does not make it ‘beyond control.’ “The fluidity of populations, their susceptibility to epidemics and contagion, is consider an asset: at a certain value or informational speed, the movement of cells turns liquid and it is this state that is identified as the most productive, engendering vertical structures that are both stable and propagating” (Terranova, 114). CAs depend on algorithms to survive.Genetic algorithms illustrate both “a mode on control and its limits” (Terranova, 115).

“Biological computation expresses a socio-technical diagram of control that is concerned with producing effects of emergence by a manipulation of the rules and configurations within a given milieu” (Terranova, 116).


Critics of the biological turn, posit that the Internet is too life-like. “To say that the Internet might be lifelike was the equivalent if sanctioning the ravages brought by rampant free-market capitalism on the ‘excluded masses’” (Terranova, 121).
Terranova furthers, “These systems are not unstructured or formless, but they are minimally structured or semi-ordered” (Terranova, 121). Terranova defines this new biopolitical plane explaining it as that which, “can be organized through the deployment of an immanent control, which operates directly within the productive power of the multitude and the clinamaen” (Terranova, 122).

Critics argue that Richard Dawkins use of ‘selfish’ acts as an “apparatus of subjectification” (Terranova, 126). Franco Berardi introduces what he deems the “unhappiness factory” that results from the unhappy gene. The CBS television program, Big Brother is an example of Berardi’s ‘unhappiness factory’ as unlikely ‘contestants’ are secluded and forced to compete and relate.

Hardt and Negri define a multitude political mode of engagement that is located outside the majoritarian and representative model of modern democracies in their relation with the recomposition of class experience” (Terranova, 129).
Multitude Franco Berardi “tendency to dissolution, the entropy that is diffused in every social system and which renders impossible the labour of power but also the labour of political organization” (130) Therefore it is critical to reconsider the exploit. That is, “hacking the multitude is still an open game.”

Discussion Questions:

In light of our ongoing discussion of control and power, how does 'free labour' work in capitalist societies? Terranova notes that free labor is not exploited labor. Do you agree with her position? How do you view free labor regarding the Internet?


Programs such as, Big Brother, offer an example of the theoretical 'unhappiness factory.' How does the video clip from Big Brother prove or disprove this theory?

4 comments:

  1. Kate writes that: “Programs such as, Big Brother, offer an example of the theoretical ‘unhappiness factory.’ How does the video clip from Big Brother prove or disprove this theory?”

    First, let’s briefly establish what the “unhappiness factory” is in the context of Terranova’s inquiry into network culture. “Unhappiness” in this context is invariably linked to “selfishness.” Terranova finds Dawkins to be key in understanding selfishness: “Selfishness is defined by Dawkins as a sociobiological tension between competition and collaboration – where the gene is like a calculating machine always weighing the advantages of collaborating or competing in order to gain an advantage of survival. If the selfish gene is a subject, it is because it thinks, and it can think only two thoughts: in a particular situation, do I increase my chances of survival by collaborating with other units? Or am I better off looking after number one to the exclusion of and in competition with others? Selfishness closes the open space of a multitude down to a hole of subjectification” (126).

    Terranova openly explains that TV reality game shows like Big Brother and Survivor exemplify, in particularly dramatic terms, the tensions of both competition/collaboration and open/closed spaces at play (e.g. the “closed space of the show” v. the “openness” created by audience authority and input through voting and the like). As a part of the unfolding drama, individual participants both willingly and unwillingly (1) relinquish their privacy, (2) adhere to strict (and often nonsensical) rules, (3) operate within a reward/punishment binary that is characterized by little, if any, middle ground, (4) struggle to become a part of a seemingly uniform group whilst still maintaining their own distinct personality (or stereotype) within the uniform group, and so on and so forth (127). Thus, we have an “unhappiness factory” which manufactures these effects and the subjects of these effects. All the while, selfishness is harvested, valued, and replicated: it is the currency of the show.

    Outside of the overly-pronounced bemusement, even outright indifference, of this particular cast of Big Brother housemates, this clip shows the typical group exercise/task in order to maintain some prize or avoid some penalty (often both at once). In terms of demonstrating (not proving or disproving, per se) the key characteristics of Berardi’s proposition about the negative effects of these structures and pressures, this clip is right on point. These people look miserable. They couldn’t muster up any excitement when they thought they had won the challenge, and it only went downhill when they learned they didn’t succeed at the task. A budget of 100 pounds for groceries for one week for a group that large is impossible, and the one male housemate threatens to withdraw from the whole thing, drawing attention to the very unhappiness/selfishness at hand. This clip exemplifies the basics of Berardi’s description, making it perhaps more difficult to spot unhappiness in shows/clips which do a better job of manufacturing and packaging “happiness” for an unsuspecting audience of fans.

    As a final note, you should all check out this article in New York Magazine which, fittingly, is titled for our reading pleasure:

    “Why Hit Reality-Show Casts Never Stay Happy”: http://nymag.com/daily/entertainment/2011/10/jersey_shore_cast_are_bored.html.

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  2. The concept of the internet as a participatory space where the user’s activity becomes labor calls into question earlier theoretical presumptions concerning a top-down hierarchal configuration of power. The power is in the hands of the user, fed into the interconnected rhizomatic network and information is aggregated through the various channels that allow this power to be productive. Is this networked labor less or more human? The knowledge based interactive communities accumulate information in the multifarious assemblages that provide an unlimited mine for corporations to glean consumer data. Thus, a free-flowing stream of data simultaneously legitimizes and stabilizes the networked existence as the networks thrive from the consistent consumption of user provided information regulated only by its nuanced protocols.

    As mentioned in the text, the unquantifiable nature of knowledge makes this kind of labor difficult to manage but it is the self-regulatory nature of participatory activity that ensures patterns of predictability. How users decide to labor provides immediate feedback to the network so adjustments can be made in real time in addition to encouraging the autonomy of the participants. This example illustrates the significance of the control society where the productive power is in the hands of the user, compared to a disciplinary society where the populations are managed through direct coercion. Of course there will always be rules, and the protocols of the specific networks arrange a set of fixed choices, however the viability of the network depends on the fluidity of these protocols, and whether the network apparatus is flexible enough to keep pace with the precipitous changes of the digital milieu. The more pliable the network, the better it can meet the demands of its users.

    This immaterial labor has significant impact on culture, as the consumptive habits of the laborers reflect cultural norms. The collectivizing of intelligence produces distinct and varied intelligence blocs that can be niched and exist somewhat autonomously, yet always be vulnerable to the possibility of rupture or exploit. Herein lies the interesting paradox of the networked society or knowledge community- despite the interconnectivity and endless possibilities for interaction and amalgamation, the nature of the user driven interface allows users the freedom to marginalize and distance themselves further from centralized regimes. The possibilities are numerous for spaces of participation and resistance which is ultimately dictated by the productive power of individual and collective usage.

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  3. Not sure what happened, but somehow my book was absorbed into the network; however, I do have Terranova’s (2000) article, “Free Labor: Producing Culture for the Digital Economy.”

    Kate asks: Programs such as, Big Brother, offer an example of the theoretical 'unhappiness factory.' How does the video clip from Big Brother prove or disprove this theory?

    In her 2000 article, Terranova critiques what we would call the upcoming reality show industry, which was nowhere near what it is today. She states “In a sense, they manage the impossible, creating monetary value out of the most reluctant members of the postmodern cultural economy: those who do not produce marketable style, who are not qualified enough to enter the fast world of the knowledge economy, are converted into monetary value through their capacity to perform their misery” (p. 52). I haven’t owned a television since 2002, but from what I understand of reality shows such as Big Brother, is that the entertainment value of the characters does not come from their happiness, but from the “real” dramas that occur between the “real” people who have agreed to be on the shows. But as my colleague Ragan Fox, who was on the 12th season of Big Brother, explained during his panel presentation at this year’s NCA, the network creates and forms the characters the audience experiences. The network chooses to highlight the moments of misery or unhappiness in the clips they decide to air.

    Unfortunately the “reality” is; unhappiness sells. The networks valorize the misery of the show’s contestants, commoditizing their feelings. The networks have realized that people who watch these shows, or their predecessors -daytime television dramas- in general are entertained by other people’s unhappiness. I think it is sad, but there are apparently lots of folks out there who love misery. In a sense, all the networks are doing is taking advantage of the preexisting affect economy and the result is not a theoretical but an actual “unhappiness factory.”

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  4. Unlike Brandon, I DO own a tv and it is usually tuned to some sort of reality programming, not just trashy made-up real-life shows but also the talk show or cooking types (which are also trashy some times, I suppose). Anyway...because I am such a huge fan of reality television, I feel compelled to respond to Kate's second question about the "unhappiness factory" which stems from the unhappiness gene.

    Terranova's discussion about genes being subjected to a moral code is an interesting one. As I often come across in my studies of human/animal relations, humans attempt to understand the inner workings of nature by using human emotions. Most of us do not understand why people do what they do. If we are all so genetically similar, why do we act so different? It cannot be nature at work. It also cannot be the environment, the nuture argument. Often persons who grow up in the same household with the same circumstances turn-out very differently. Some people rise above adversity; others sink far below it. What is going on here? To answer this question, we fall back on our lay knowledge of "science." It MUST be in our genes! We are genetically similar, but we are not the same (identical twins beingthe exception here). This is a valid explation for biological aspects of difference, but it does not and cannot account for personality or moral differences. As Terranova notes from Dawkins, "genes have no 'purposes', they obey obscure impulses dictated by complex chemical laws. With no sense of purpose, arguably, there is no self and hence no selfishness" (p. 126). The guy in the Big Brother clip is not selfish because his genes made him so. He is attempting to win a game where "competition and collaboration" exist in an equally advantageous state (at least in the beginning of these reality games). Of course, he might just be a big ol' jerk who has sharing issues. But, that is another reality show.

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