Capital at the Brink: Overcoming the Destructive Legacies of Neoliberalism

Governmentality, Neoliberalism, Risk

One of the ways in which scholars have approached neoliberalism and risk has been through governmentality theory. Foucault defines governmentality as “the way in which one conducts the conduct of men.” [4] This definition is echoed by others who have followed Foucault in theorizing about government. [5] Governmentality theory not only focuses on government writ large, but on micro-processes of government as well. Governmentality bridges the analysis of a broader biopolitics of governing the conduct of populations to that of the anatomo-politics of the governing of individuals and selves and their conduct. [6] As such, governmentality examines how power flows function apart from the State and considers governing practices. [7] Those who have used governmentality theory to address present social and political conditions have concentrated on a relatively recent iteration of government, advanced liberal or neoliberal governmentality.

Those subscribing to governmentality theory explain neoliberalism by grounding it in an older liberalism and this liberalism’s accompanying preoccupation with the free market. In his examination of the eighteenth century roots of neoliberal governmentality, Foucault [8] argues that the market became the guiding metaphor for liberal governing. The market was understood to obey natural laws, laws that expressed themselves in prices that rose and fell with supply and demand. In order for these natural laws to play themselves out, those operating within the market were to be given as much freedom as possible. This market freedom was extended to an evaluation of governmental practice such that the free market became the basis for the formation of a governmentality stressing freedom. Government was no longer to impose power, but to manage freedom. The free market economy and liberal state ended up reciprocally supporting one another in their commitment to managing freedom.

These principles of eighteenth century liberalism find a renewal in twentieth century neoliberalism. With the advanced liberal or neoliberal rationalities of government prominent in the late twentieth and early twenty-first century, the power of government finds justification in “artificially arranged or contrived forms of the free, entrepreneurial and competitive conduct of economic-rational individuals.” [9] In this context, the governed, free, neoliberal subject becomes what Foucault variously calls homo economicus, “an active economic subject” [10] and an entrepreneur of the self. The economic subject must think about the self and others as engaged in competition where choices must be made about scarce resources. Notions of supply and demand and investment-costs-profit become the way the individual relates to the self and then outward. The entrepreneurial self is invited to employ “certain management, economic, and actuarial techniques” [11] in everyday practice. As such, in neoliberalism, the market is applied to traditionally non-economic social phenomena such that subjects consistently operate through this entrepreneurial lens and employ its techniques in their conduct. [12]

Neoliberalism and Risk

To function as an entrepreneurial self is to necessarily consider one’s future. How this future is understood and how decisions are made about this future take on particular contours within neoliberalism. Given the neoliberal subject’s freedom to function as an entrepreneurial self, they are simultaneously responsible for dealing with the risks of potential dangers and misfortune attached to this freedom as well. How is risk understood within the framework of a neoliberal governmentality?

Governmentality theorists have argued that risk can be understood as a governmental rationality, a particular way of thinking about and responding to governmental problematics. These rationalities render reality in a particular way so that governing may occur. [13] Rendering reality in terms of risk serves as an expression of a specific governmental rationality tied to governing the future. Risk management becomes the rational response to risk for its “identification, assessment, elimination or reduction of the possibility of incurring misfortune or loss.” [14] Assessing and managing risk engages a precarious future. O’Malley affirms the future orientation of risk in arguing that risk produces “the state to be avoided, the state to be achieved, and the acceptability of ways whereby the two conditions should be governed.” [15] Within neoliberal approaches to these future conditions, risk and risk management take on a specific shape characterized by an emphasis on individualism, a privileging of a scientific, actuarial matrix of expertise and its accompanying bias toward a quantitative epistemology.

First, in neoliberalism, risk is predominantly an individual matter. If the neoliberal self is an entrepreneurial self, then this self must necessarily be induced to adopt a particularly individualistic rationality with respect to risk. The entrepreneurial self’s more individualized approach to risk contrasts older approaches to risk in the more collectivist welfare state. As Rose points out, risk used to be understood as social. [16] Early forms of statistical reasoning in nineteenth century France and Italy were deployed in the service of dealing with collective risks attached to public security and public health. [17] In the nineteenth century, establishing security over and against various forms of risk meant becoming part of social organizations like trade associations and, at a broader more compulsory level, national social insurance programs. Risk was collectivized within these types of social structures. [18]

However, in neoliberalism, this collective approach to risk has been challenged under the pressure of free markets that require individuals to be responsible for their own well-being. As an example, social insurance programs have come to be understood to foster a culture of dependence and laziness. Neoliberal subjects are encouraged to consider their individual futures rather than depend on social entities for what is to come. Lazzarato goes so far as to argue that neoliberal subjects exist in a context permeated by “permanent insecurity and precarity.” [19] As a consequence of subjects being left free to address the promise and peril of their respective futures, entrepreneurial selves are positioned to adopt a rationality of risk and risk management. Subjects begin to operate in a context characterized by, what O’Malley calls “prudentialism.” [20] This prudentialism places the responsibility for managing risk on the individual who can no longer rely on larger social collectives to deal with risk. Risk and techniques for managing risk become privatized and individuals are encouraged to govern themselves responsibly in addressing risk, i.e. to act with prudence. The rational individual practices a rationality of risk management in order to act prudentially and successfully deal with risk.

A second aspect of the relation between neoliberalism and risk concerns a privileging of what might be deemed a scientific, actuarial matrix of expertise. Although the entrepreneurial self is incited to take responsibility for risk without relying on a broader collectivity, neoliberalism makes particular forms of expertise readily available. Entrepreneurial selves are invited to take advantage of this expertise as a way to be responsible and this expertise becomes one of the ways by which responsibility is understood. Governmentality theorists have suggested that expertise serves as one of the primary ways in which governmental objectives are translated into everyday experience. Experts assert truth claims and dispense pedagogical resources as a way to incite individuals to act in keeping with governmental objectives. For example, experts might teach subjects how to achieve greater earning capacity or improved health. Expertise makes government possible and legitimizes it by mediating governmental objectives such that “self regulatory techniques can be installed in citizens that will align their personal choices with the ends of government.” [21]

In most cases, the power to define what constitutes risk and how it ought to be addressed is held by those with social power. In neoliberalism, experts who were once respected and subsequently possessed relative autonomy in the welfare state have their expert knowledge critiqued. [22] With respect to risk, older forms of expertise become substituted for a scientific, actuarial matrix of expertise.

Although Beck does not subscribe to governmentality theory, his discussion of scientific expertise and its relation to risk is helpful here. Beck asserts that, in the context of risk, one of the foremost sites where this social power is expressed is the scientific community. [23] For him, risk has come to only be detected in the contemporary situation through the extended senses of the scientific. Scientific senses render risk visible. Beck goes so far as to say that if a risk cannot be scientifically recognized, then it ostensibly does not exist. Science has the social power to dictate what constitutes risk and how the public perceives these risks. Scientists serve as the experts whose expertise is incontrovertible. Proof of risk’s existence and what constitutes and causes risk become the purview of these scientific experts.

In the overwhelming majority of instances, the sciences employ quantitative methods to render risk visible. This methodology assumes that “scientific methods of measurement and calculation are the most appropriate way to approach risks descriptively, explanatorily and prognostically, and importantly, also politically.” [24] With this emphasis on the calculative approach to risk, Beck echoes Foucault’s discussion of a more specific kind of scientific gaze, the medical gaze on the body, a quantifying gaze that made “it possible to outline chances and risks; it was calculating.” [25] These quantitative methods applied to risk sit at the core of a specific type of science, actuarial science. Actuarial science is expressed in practice through actuarialism. This actuarialism can be characterized by an emphasis on non-invasive forms of routine surveillance, a greater and greater speed in the acquisition of information for the purpose of managing populations, an approach to risk that is heavily based in statistical knowledge, a morality that is grounded in statistical norms and a production of risk that engenders increasing numbers of risks. [26] Actuarial science produces mountains of quantitative data as a way to manage the risks that it continuously produces and makes intelligible.

Because science and actuarial science make risk visible and perpetuate risk, they bring along an attendant epistemological assumption that perceives risk through a causal frame. Beck argues that,

As the expertise of science presents these cause-effect relations with respect to risk and persuades individuals to believe in these relations, this causal perspective necessarily fosters a zone of responsibility for those subject to these discourses. If risks are grounded in causes, then responsible interventions can occur before deleterious effects ensue. For subjects to refuse to perceive risk through this causal lens is to be irresponsible. For Beck, [28] ordinary citizens are not allowed to question these assumptions or to redefine these questions surrounding risk for themselves. They must adopt this causal approach to risk and subsequently practice responsibility for managing risk according to the definitions offered them by said experts. As non-experts with more limited knowledge, they have responsibility foisted upon them in the midst of myriad variables.

As part of this shift from older forms of expertise toward a neoliberally-inflected, scientific, actuarial expertise, a broader commercial culture of risk arises. The risk industry and various professions linked to minimizing, managing and preventing risk feed concerns about risk by creating and marketing various products that presumably allow us control over our own fates. [29] The rationality fostered by the risk industry generates “a relentless imperative of risk management not simply in relation to contracting for insurance, but also through daily lifestyle management, choices of where to live and shop, what to eat and drink, stress management and exercise….” [30] The risk industry not only touches the outer person, but the inner person as well as it capitalizes on risk management techniques linked to self-esteem and empowerment. The risk industry encourages subjects to take responsibility for themselves by operating within the parameters of efficiency and cost-benefit analysis as a way to incite them to a semblance of agency.

The neoliberal culture of risk becomes amplified and exacerbated such that few areas of life remain untouched by its perpetuation of a risk management rationality. Personal choices come to be increasingly oriented around risk, a risk that is defined by scientific, actuarial expertise and mediated through the risk industry. Risk experts functioning within the risk industry adopt an incontrovertible monopoly on risk assessment and governance as they incite individuals to responsible action. [31]

As the scientific, actuarial matrix of expertise operates in the cultivation of responsibility, it works in and through a third element of neoliberalism’s relation to risk, technologies of government. Risk and techniques for risk management are produced by and mediated through technologies of government. In governmentality theory, technologies of government do not necessarily function as direct connections from governmental authority to individuals and groups. Rather, they exist as part of what Rose and Miller perceive as “the complex assemblage of diverse forces” that operate to instantiate the interests of government in those who make decisions. [32] Technologies of government play an important role in realizing governmental thought. [33] They serve as the various ways in which individual conduct, thinking, and goals are shaped and normalized for the purpose of governmental goals. [34] These technologies may be more formal with respect to forces circulating around law and finance or they may be “humble and mundane” [35] in operating through the everyday mechanisms of things like calculations, surveys and speech communities. [36] Technologies of government are not essentially linked to specific forms of governmentality. Rather, technologies only become important in their relation to ideas and practices as certain manifestations of governmentality facilitate and pattern these various practices within their respective techno-social relations. [37] What is significant for this discussion is “how a given technology or space is combined, at a particular point in time, with various discourses, political and ethical ideals and already established habits to form a loose assemblage of governmental agency.” [38] Technologies of government become one component within a broader governmentality.

Following from the discussion above, an important part of engaging risk and managing risk in neoliberalism revolves around technologies of government linked to quantitative or calculative rationality. Entrepreneurial selves operating in a neoliberal context function as, “risk-assessors, performing the felicity calculus in an attempt to plot the probable and possible consequences of their actions.” [39] Quantifying technologies of government allow these selves to determine what is in their best interests in the present and for the future.

Greater reliance on quantification has led to an increasing consciousness of risk. [40] As alluded to above, in their deployment within science and actuarial science, numbers play a vital role in producing risk and dealing with risk within liberal and neoliberal government. They enable certain knowledges and the decision-making processes that follow from these knowledges. Subsequently, numbers both constitute risk and become the basis for managing risk. Numbers are also important for the communication of risk. With their ability to momentarily stabilize various dynamic processes, numbers allow for a consideration of probability. Probabilities invariably connect to assessing various degrees of risk. This kind of thinking renders risk both visible and calculable in the present. Risk becomes “disciplined, by means of the statistical intelligibility that the collective laws of large numbers seemed to provide.” [41]

Numbers typically inform risk assessments. These risk assessments become pedagogical tools that not only teach the entrepreneurial self which decisions to make, but how to think about decision-making. This how is often linked to quantification such that risk assessments further what might also be understood as an audit rationality. The audit rationality subsequently becomes an important way that entrepreneurial selves govern themselves. To practice auditing and to be made auditable is part and parcel of functioning within spaces of risk management. [42] Numbers also begin to shape the type and nature of choices afforded the entrepreneurial self. Under the influence of the economic freedom of neoliberalism, choice is rendered calculable as subjects attempt to rationalize and optimize their activity. [43] These choices are presented against a backdrop of risk that is itself buttressed by quantification. Numbers subsequently further the subject who can be “rendered calculable to others and to him- or herself in terms of numbers.” [44] Numbers transform individuals into calculating selves who subsequently calculate, predict and evaluate their own actions and the actions of others, especially within the context of risk. As such, numbers come to govern individual behavior. [45]

To combine the ideas of neoliberalism and the free entrepreneurial self, that self’s relation to scientific, actuarial expertise and technologies of government that further shape this self’s relation to risk is to see the pervasive nature of risk in a neoliberal context. Within this context, Rose sees the risk industry generating a constant stream of imperatives inciting subjects to carefully manage risk in multiple social domains. [46] This risk industry might be comprised of insurance, security and self-help businesses. However, discourses of risk also find themselves into leisure space as well. In the remainder of this essay, I explore the video game, as one “humble and mundane” site within which risk and risk management are expressed as the right way to attempt to govern an unknown future. [47] The essay takes up how the technology of the video game combines with neoliberal discourses on risk to serve as one component of a broader, loose assemblage of neoliberal governmental agency.

Quantification and Risk in the Video Game

Of specific interest to me in this paper are questions addressing how risk and risk management are made intelligible through the technology of the video game. It would be an exaggeration to argue that all video games invoke a specifically neoliberal approach to video games. However, many popular video game genres including the music, real time and turn-based strategy, first person shooter, and role playing game genres can be more deeply understood through this neoliberal lens. In order to illustrate how a neoliberal rationality of risk expresses itself concretely, I turn specifically to another genre where this rationality appears, the sports video game genre. More particularly, the remainder of this essay looks at one example by analyzing SI Games’ popular soccer management simulation, Football Manager 2010 [48] (hereafter FM10), from a critical perspective. Although FM10 certainly cannot represent the diversity of video games, many of the game mechanics discussed below can be applied to other sports games and games in other genres.

In FM10, the game’s users are not merely football managers, but are simultaneously positioned as entrepreneurial selves who must manage risk. Users must function as entrepreneurial selves by managing risk by deploying various scarce resources to move the club along the road to success and by locating important relationships between causes and effects. However, not only are users risk managers, but the game also positions them as subjects of risk. Users must accomplish these objectives even as they are subject to risk in being under constant surveillance from the club’s virtual supporters and chairman. The game subsequently naturalizes an existence as a neoliberal entrepreneurial self who must deal with risk while simultaneously being subject to risk.

Users as Risk Managers

First and foremost, users are positioned as risk managers. In order to achieve the game’s goals of winning championships and in some cases, generating virtual revenue, users must analyze the quantified attributes and performances of virtual athletes to assess present game events and plan future in-game choices. As such, the user becomes aligned with a particular approach to risk management characterized by an engagement with numbers at nearly every turn.

Statistical Productivity

The way that FM10 mediates game information mirrors other forms of new media in the sports media complex that provide quantitative indices measuring typical categories linked to either a given athlete’s bodily characteristics or production. [49] Professional teams will often evaluate potential additions to their squads based on heights, weights, and speed or on previous statistical performance in another context. FM10 gives users access to these kinds of measurements in full force. Every player’s profile screen features his height, weight, age, wages and estimated value. In addition, FM10’s game engine quantifies myriad statistics that track the productivity of individual players as it simulates matches. Among these statistics include game appearances, goals, assists, man of the match awards, yellow and red cards, tackles succeeded and attempted per game, key tackles, passes completed and attempted, pass completion percentage, key passes, intercepted passes, runs into space, number of times caught offsides, dribbles per game, shots on target percentage, fouls, fouls against, penalties taken and scored, average minutes per goal, minutes since last goal, headers won and attempted, key headers, total distance covered and distance covered per ninety minutes, mistakes leading to goals and total mistakes, and condition percentage. The game engine uses these numbers in a given match to come up with a match rating. These match ratings are then aggregated and averaged to provide the user a sense of that player’s performance over the course of a given season. Alongside the average rating, users can find out a player’s lowest and highest ratings of the season.

As users play a match, the game continues tracking all of these statistics and makes them readily available at the click of a mouse button. It is entirely possible to play the game like a real world manager by watching the action unfold over the course of ninety real world minutes. Users can literally watch their players move, shoot and pass in a 3D representation of the match. Much like real world managers, users can simply observe how their players perform and adjust their tactics accordingly. If a user notices shots flying past the post on a consistent basis, that striker might become a prime candidate for a substitution. If a user sees a midfielder aggressively committing too many fouls, that player’s instructions can be modified to make him more cautious. Playing the game this way entails observing the action on the pitch and responding accordingly. However, for users to play a whole season this way would be incredibly time consuming and potentially test any user’s patience.

Choosing to play FM10 in this pedestrian, real world style ostensibly deviates from the implied intention of the game’s design. FM10’s football universe includes 117 leagues yielding a massive number of clubs for users to potentially manage. The manageable teams range all the way from the globally popular such as Spain’s, Real Madrid, to the regionally obscure like Singapore’s, Balestier Khalsa FC. FM10 allows for the possibility that a team from, for example, one of the English league structure’s semi-pro divisions could one day compete in the same division against Premier League giants, Manchester United and Chelsea. Although Sports Interactive allows users to manage the world’s biggest clubs, the company actively encourages the fantasies of supporters of lower division clubs. FM10’s official website features a discussion forum section dedicated to so-called lower league managers who can share strategies and another sub-section for stories from these managers who have taken their clubs from virtual local obscurity to the heights of glory in world football. The existence of this dedicated forum area suggests the developers’ desire to see users achieve successes that would be near impossible in the real world. One of the obstacles to this success might be the time investment required if users played each match in real time. To adopt this approach and make the shift from the sixth tier of English football in the Blue Square South to the top tier of the Premier League would require users to play at least 222 games (not including exhibition and cup games) and work through five seasons of play. For users to achieve this goal by managing matches in real time would mean nearly 20,000 minutes or upwards of 333 hours playing the game. Putting in this time is certainly possible, but highly unlikely, for the overwhelming majority of users. It would also make users’ rags-to-riches experiences, experiences that serve as official and unofficial marketing material, extremely rare given the time investment required.

SI has dealt with this time issue by allowing users the chance to quickly simulate a large portion of the match. Users have the option of managing a match, but limiting what they see in the 3D representation to only goals or only key highlights (free and corner kicks, important tackles, excellent saves, yellow and red cards, narrowly missed shots on goal and the goals themselves). Restricting the visual representation of events in each match dramatically reduces the time users need to complete it. Rather than requiring ninety minutes in real time, matches can now be finished in five or ten minutes of real time. The sharply accelerated clock has some consequences for how the user’s experience unfolds. With the match’s virtual minutes flying by, users are unable to see what their players are doing outside of these key highlights. Accelerating the clock means skipping over events the game does not deem highlight worthy.

In order to make the unseen visible as and help users discern what is happening between these visually represented highlights, FM10 constantly tracks the aforementioned statistics and provides users access to these numbers. Users see what cannot be seen by looking at the data the game produces. As a result, the game positions users to consistently be accessing quantitative data as a way to gauge how well their team and individual players are performing. Users must attend to team performance statistics like what percentage of time the team possesses the ball and/or how often they have possession in a given area of the field, overall pass completion percentage and how many long shots have been taken. Users must also carefully examine individual statistics as well. These statistics provide greater insight into specific player performances in a given match. In addition, users also see a percentage measuring a player’s physical condition. The percentage slowly falls throughout the match to reflect a player’s level of fatigue or suddenly drops to indicate a short term or potentially long term injury. Consequently, the numbers mediate events that, due to a user’s time constraints, cannot be experienced personally in keeping with how numbers function at a more general level. [50]

Even though users might not be able to witness various forms of potential misfortune and loss to their teams or their players directly, the numbers the game generates renders these dangers visible and amenable to intervention. In this respect, the computer becomes the virtual quasi-scientific, actuarial expert producing the data users can employ to make decisions. As users engage this data, they invariably perceive potential threats to their teams in accordance with the risks produced by the computer.

The highly quantified nature of the match experience furthers the instantiation of a neoliberal approach to decision-making. By presenting users with an avalanche of numbers, FM10 positions them to function as entrepreneurial selves who must manage risk by making constant assessments of the data being presented to them. Invariably, this data represents the existence of threats or potential threats to the user’s team. Users are positioned to engage this data for the causes of the effects that are the game events. Users may not be able to see their central midfielder successfully breaking up opposition attacks with skillful tackles, but the data allows them to make this conclusion. Users may not be able to see their club being overwhelmed by the percentage of an opposition’s possession, but the displayed percentage that has been calculated by the simulation can move the user to switch to a counter-attacking strategy to absorb the pressure. Users may not see their team’s lack of success in the attacking zone, but they can look at the shot count breakdown and instruct their players to work the ball into the penalty area rather than have them take longer shots from distance. By checking on scores in other matches, users might instruct the squad to adopt a more attacking or conservative mentality. These statistics become the causes for making tactical changes to the team’s playing style or formation that potentially yield the desired effects of victory.

Potential risks also operate on an individual player level as well. Users may check the data to see how many fouls a given defender might be committing and instruct that player to defend more cautiously. Conversely, taking advantage of a poor opposing defender might mean asking a winger or a forward to run with the ball more often in hopes of drawing more fouls and potential yellow or red cards. Examining how many shots on goal a given striker may have successfully put on target could mean the difference between leaving him in the game or inserting a substitute. One of the most important numbers users engage in a match is the conditioning percentage. As a player’s conditioning percentage drops throughout a match, he becomes less effective. For users to fail to respond with a substitution could mean tired players committing costly mental errors or slightly injured players turning a minor knock into something much more serious. All of these risks come together in the potential for a loss, a downward step on the league table and the potential threat of a lost virtual job.

Quantifying the Body

Although some exceptions exist, like the aforementioned player condition percentage, the statistical tracking that occurs during matches in FM10 mirrors other types of quantitative representation in media across the sports media complex. By tracking the production of an athlete’s labor, FM10 generates data that looks very similar to that which can be found on websites and on television broadcasts. However, differentiating FM10 from other forms of measurement in these media is the game’s preoccupation with quantification beyond a given player’s direct on-field productivity. Where the conventional statistical categories still mediate a player’s labor production and overall contribution to a squad’s success or failure, FM10 quantifies variables that have no real world correlation. To quantify that which really cannot be truly quantified is to place a grid of intelligibility over the seemingly immeasurable and position it within the parameters of risk management to an even greater degree. The user as entrepreneurial self must navigate the risks of decisions grounded in the quantification of intangibles linked to the athletic body and its potential.

With respect to individual players, each of the more than 297,000 football players in the database is represented by a series of attributes that mediate that player’s physical composition and talent. Again, the computer as expert provides this data to the user. The attributes for each player are divided into three categories: mental, physical and technical. First, mental attributes represent a player’s ability to think on the pitch and provide a rudimentary psychological profile. Players with high mental attributes will continue to give their maximum effort no matter whether the team is favored to take an easy victory or facing near impossible odds. Mental attributes also indicate how players read and react to situations as the match unfolds. These attributes include variables like anticipation, creativity, determination, positioning and work rate. Second, a player’s physical attributes represent his body’s ability to move. Physical attributes include acceleration, jumping, natural fitness, and strength. The game’s manual suggests that physical attributes are most important stating that if a player has sound physical attributes, “he’ll be able to play a competent game and make sure he isn’t embarrassed much” and that “he has the required attributes to be a solid footballer.” [51] Third, technical attributes most directly represent what might be approximated as a player’s ‘acquired’ football skills. Technical attributes include dribbling, free kick taking, passing and tackling. The manual states that high technical attributes differentiate the best players from the above average and average players. Elite players will always possess high ratings in technical attributes. The cumulative effect of these attribute categories means that every player in the database is assigned a rating of 1-20 for each of the game’s forty-two player attributes. These attributes also combine with the level of competition in the player’s league to provide him with a valuation. This valuation becomes a guide outlining roughly how much a team would have to pay to acquire his services. In order to understand how their chosen club is performing, users must engage these different attributes and their relationship to the attributes of opposing teams.

The sum total of the way these numbers constitute the reality of the game world constructs the athlete as what Rose calls a “calculable other.” [52] This calculable other becomes a scarce resource users deploy in the game. The real world athlete becomes subject to the ratings systems in place in digital sports games; the user engages with that athlete almost entirely on the basis of that athlete’s enumerative representation. To look at the individual player profile screen and its quantification of the athletic body is to see a bridge between a scientific cause-effect approach to risk and governmentality theory’s connection between the market and an entrepreneurial approach to risk. By quantifying the player into a series of respective attributes, the athletic body become subject to the purview of the scientific, actuarial gaze as its component parts are dissected and made available for scrutiny. As stated above, for users to ignore these attributes would be to fail to adequately assess potential causes for the effects that ensue during matches.

In order to play the game in a responsible way, the user must engage the game world in the same way that Foucault [53] describes how liberal governments engaged those they managed. In both instances, statistics allow for surveillance, analysis and intervention into the lives of populations. Respective virtual and material individual bodies became subject to the statistical such that numbers became the basis for distinguishing between “the more or less utilizable, more or less amenable to profitable investment, those with greater or less prospects of survival, death, and illness, and with more or less capacity for being carefully trained.” [54] To assess whether a given player is more or less utilizable, a sound investment, has a better chance of thriving on one’s squad, whether he is heading towards the end of his career, might be prone to injury or has the potential to be managed successfully is to function as an entrepreneurial self. The virtual athletic body becomes a potentiality from which the user must maximize to extract the greatest value. To look at the different attributes of various players is to be able to compare them through the numbers the game provides. Given that the player serves as a resource, and a scarce resource when it comes to the game’s best players, the user is positioned to act as an entrepreneur who must responsibly deploy this resource for a set of desirable ends.

In FM10, the entrepreneurial self who is the user is positioned to deploy quantitative data to make risk-based decisions that not only potentially yield success, but also guard against loss and failure. As a result, turning athletes into calculable others renders them subject to risk and risk management practices through the mediation of their respective abilities in the number. For users to fail to perceive the importance of these numbers is to fail to play the game responsibly. Invariably, ignoring player performance on the pitch or the players’ respective attributes off of it will mean being fired from one’s managerial position and potentially without an ability to continue playing the game.

User as Subject to Risk

Not only does FM10 position users as risk managers, but users themselves become subject to risk management. Given their place as managers functioning between the virtual playing staff and virtual boardroom, users are responsible to the authorities above them who have the ability to continue to allow them to manage the squad or to dismiss them from their managerial position.

In FM10, individual players, teams and club finances quantified for careful risk management. However, the user’s alter ego is also quantified as well. Users can examine their manager’s profile for information about their existing contract, the virtual wages they are earning and their general knowledge of certain areas of the global football landscape. This managerial profile is also supplemented by a page dedicated to a manager’s statistics. Data on this screen is aggregated from player purchases and sales, the amount the manager has earned over the course of the game, match performance, league and cup wins, goals scored and conceded, the number of awards won and the time spent at the current club. This screen also reveals the user’s Hall of Fame ranking, an in game sorting of managers past and present. Users can compare themselves to managers with their chosen nationality, managers in the nation in which they are competing, and managers continent-wide and worldwide.

More interestingly, the user’s manager is rated using the same 1-20 scale that is employed to rate specific player attributes. However, rather than rating the manager’s physical characteristics and talent, the user’s manager is rated in the areas of player loyalty, domestic player bias, financial control, hands on approach, squad discipline and tactical consistency. These categories relate to the manager’s mental approach and shift and change depending on the decisions the user makes throughout the game experience. Although it is difficult to tell whether these attributes play an important role in shaping how the game unfolds, it would seem that club chairmen would take these numbers into account in deciding whether or not a manager should be hired or fired.

In addition to this quantitative information, at the beginning of each game month, users are sent a message from the chairman with a synopsis of the previous month’s performance. This message reports on how the chairman perceives the club’s position in the league, recent match outcomes and whether the club turned a profit or suffered a financial loss in the preceding period. From this screen, users can click and access information about their overall performance with respect to competitions, transfers, individual match performance, individual player performance and finances. Within each of these categories, a horizontal bar graph identifies how well the user is performing over and against the expectations established by the club’s chairman and fans. These performance graphs are subsequently used to determine whether users keep their jobs or are relieved of their duties. The reasons for a firing might be anything from poor match results to unwise financial decisions to irresponsible appeals to the chairmen for more resources of various kinds.

For FM10 to quantify the user in this way is to constitute the user as an entrepreneurial calculable self within a broader context of quantification and risk. With the ascendance of quantitative methods employed in neoliberal governing, Rose notes that we see the rise of the person operating within these boundaries—one who can be “rendered calculable to others and to him- or herself in terms of numbers.” [55] Dean agrees with Rose’s contention in suggesting that technologies of performance linked to numbers transform professionals into “‘calculable individuals’ within ‘calculable spaces’, subject to ‘calculative regimes.’” [56] From Dean’s perspective, the calculated self performs in keeping with the standards established under regimes of calculation instead of freely acting as they wish. This appears to hold for FM10 as users come to understand themselves as subject to risk through their managerial profiles and performance graphs. Users cannot evaluate players and their own performances based on their own criteria. Rather, they are positioned to make decisions in accordance with their status as calculable selves who, by virtue of the quantified nature of the experience, are themselves subject to risk management.

As such, not only do users virtually responsibilize the players under their managerial purview, but they themselves become responsibilized through the numbers assessing their performance. Numbers move people to be responsible for their own conduct in that “they turn the individual into a calculating self endowed with a range of ways of thinking about, calculating about, predicting and judging their own activities and those of others.” [57] Managers working from these principles rationalize employee performance via quantification while employees working under these managers attempt to maximize their production quantitatively. In FM10, this internalization of a calculative rationality functions both ways.

In some respects FM10’s managerial profile feature completes a circle that began with the quantification of the athlete into a series of ratings. Whereas prior digital sports games enumerated only the athletes and their performances, to have the user’s virtual managerial self quantified extends this enumeration to users themselves. As they submit themselves to being measured and assessed, users become virtual athletes in their own right subject to the same quantitative discourses and their attendant links to risk and risk management as the athletes being represented. As such, users not only govern through discourses of risk, but are also positioned as potential risks themselves. By positioning users to make decisions based on quantitative information, FM10 naturalizes an entrepreneurial self who must deploy a risk management approach to future outcomes. By positioning users as quantified information, FM10 naturalizes an entrepreneurial self who is responsibilized and subject to risk management.

Even as FM10 quantifies all of this information and positions the user as an entrepreneurial self engaging risk, it also seems possible that the grid of rationality placed over this virtual football world may be eliding any potential failure of neoliberal political rationalities. FM10’s persistent imperative to feed the user numbers cloaks the idea that some things cannot be understood apart from quantitative information. Through the numerical assessment of a player’s mental abilities or the user’s loyalty as a manager, FM10 transforms the subjective into the apparently objective via enumeration. As such, playing the game becomes an exercise in engaging both calculable risk and believing the notion that the incalculable can always be rendered calculable. This constant calculation affirms Beck’s insistence on the contemporary “compulsive pretense of control over the uncontrollable, whether in politics, law, science, the economy or everyday life.” [58] FM10 illustrates this pretentious control as it positions users to conduct themselves through calculation on multiple levels.

Although it is certainly possible for users to engage in “counter conducts” [59] and favor a given virtual athlete as a consequence of an emotional attachment to his/her real world counterpart, these kinds of interactions would appear to be infrequent. It is also entirely possible to play FM10 against the intentions of the virtual universe’s chairmen, coaches and players. Some users do find great pleasure in creating a managerial profile, appointing themselves as manager of one of their most hated rival teams with this profile and then running the despised club into the financial and footballing ground. These users then turn around and create a new managerial profile, appoint themselves as manager of their favorite squad and enjoy taking advantage of that defanged rival. Other users might attempt to create teams made up of only a certain nationality, to sign players from specific countries or form a squad from players with interesting names.

Still others may resort to decision-making based in uncertainty rather than risk. Where governing through risk attempts to render the future objective through quantification, governing through uncertainty focuses on the “singular, infrequently recurring or unique.” [60] Uncertainty differs from risk in that it does not employ quantitative measures as evidence in rational decision-making. Instead, professional judgments, rules of thumb, and experience take precedence over the statistically-based measures more conventionally associated with rationalities of risk. O’Malley is careful to argue that spaces of uncertainty are increasingly discursively absorbed into risk, but maintains that uncertainty still plays a major role in grounding practice. Even as the game positions users to make decisions in accordance with risk management, they may mix uncertainty-based and risk-based decision-making approaches in hybrid configurations as they play.

Conclusion

To be sure, the video game does not provide a totalizing expression of neoliberalism nor does neoliberalism provide a totalizing explanation of the video game. Rather, video games serve as a space in which specific neoliberal ideas manifest themselves. Any neoliberal ideas that appear in a given video game may be combined and recombined with other types of governmental rationality depending on the game in question. However, at a general level, a governmental approach to the video game reveals neoliberalism’s cultural work within some of its common game mechanics, especially with respect to assessing and dealing with risk through discourses of calculation.

For the video game to naturalize a risk management oriented around calculation is to naturalize broader neoliberal discourses of scientifically and actuarially-inflected risk management. The video game mediates this cause-effect understanding of risk and justifies this understanding throughout multiple layers of its gameplay. Beck locates the consequences of this understanding by arguing that it enables the domination of “the ‘mathematical morality’ of expert thought,” [61] a morality that, when combined with a public discourse informed by it hides itself morally and politically. This mathematical morality implies that right ethical decisions are those informed by quantitative data provided only through expertise. Additionally, by rendering the overwhelming majority of information in the game through a quantitative lens, the video game positions the user as homo economicus. Foucault [62] argues that serious problems derive from an economic approach to life. He questions why the scarce resource model should be consistently applied to a diversity of non-economic situations. Even more problematic, for him, is the idea that rational conduct is only rational when articulated to this economic conduct.

Even as neoliberal risk management appears most prevalent in the contemporary video game, one wonders how video games could change as a consequence of increased social networking, social networking that Terranova [63] characterizes as production occurring outside of market mechanisms. This non-market production becomes oriented around cooperation rather than the competition that has characterized neoliberalism. She argues that social relations in this space revolve around treating others as human beings instead of actors within a market. Terranova positions these forms of production as a potential check on neoliberal governmentality. Perhaps the individual approach to risk in neoliberalism will be superseded by the cooperation afforded by social networking technologies.

However, even if cooperation should become the hallmark of future video games as a consequence of social networking, it would seem that vestiges of the neoliberal governmentality discussed here would remain, at least in some capacity. As such, it would appear that video games could continue to be situated within a “diagram of post-disciplinary logics of control … based upon a dream of the technocratic control of the accidental by continuous monitoring and management of risk.” [64]