When Smiles Become Surplus Value
URBAN SCREENS, AFFECTIVE LABOUR & THE HUMAN BODY AS DATA PACKAGE
Master Thesis by Roselinde Bon Supervisor: Niall Martin
Date: June 12, 2018
Abstract
In contemporary urban environments, there are numerous types of digital screens that facilitate the datafication of human affect by actively eliciting or passively collecting feedback from the public. The public often interfaces with such screens without being aware of the data they may be supplying. Therefore, the aim of this research project is to contribute to an improved legibility of data collection moments by analysing how networked urban screens shape the affective labour processes that enmesh the mobile and reactive body into the digital economy. Examples of affective strategies are asking consumers to personally review a service through a selection of emoji, requiring consumers to smile to confirm their payment, or monitoring which ‘demographic types’ of consumers smile at a specific advertisement. The corresponding processes that enmesh the body into the digital economy prove to be different in every case, but what lies at the core of every screen-facilitated affective labour setting is the modification of communication into a capital relation. As the exchange of affect becomes the most critical strategic asset in sustaining reputations and privileges, even love and friendship are being subordinated to the digitized capitalist circuit.
Acknowledgements
I would like to thank Dr. Niall Martin for guiding this project from the very beginning, when my only lead was a toilet review screen. Another special thank you goes to my friend Ke Ma for generously assisting me with finding and translating documents that proved vital to my second chapter of analysis. Finally, I wish to express my gratitude to friends and family, especially my parents, for the continuous encouragement during this master’s programme, including the final stages of writing this thesis.
Index
I. Introduction 4
II. The Toilet Review System at Changi Airport
Digital Reputations and Asymmetrical Social Dynamics
The Habituation of Social Media Logic
The Bodily Matter of Affective Labour
13 14 16 19
III. Smile to Pay and the Sesame Credit System The Pentagram of Networked Citizenship Sesame Credit as a Dataveillance System
The Spatial Body in a Data-Sensitive Environment
The Affective Body in Sesame’s Digital Reputation Economy
22 25 27 28 30
IV. Exterion Media’s Digital Billboards at Dutch Transport Hubs The Cognitive Worker in a Cloud of Signs
The Affective Body in the ‘Anonymous’ Crowd
34 38 40
V. Conclusion 43
Works Cited 46
I.
Introduction
That the social sphere has become the primary domain for data mining, and that there are now a plethora of commonly-used data collection strategies to extract information from the public, is a matter of common cultural knowledge. Yet, even after the Cambridge Analytica revelations (Cadwalladr and Graham-Harrison), the full extent of these mining moments is not always fully understood or fluently ‘read’ by everyone, notably in terms of the extent of feedback they may be supplying. Familiar examples of data collection moments are simple acts and expressions of affect: posting a status, liking or reacting to a post, and clicking on links on a social media platform like Facebook or Instagram (Nield; Hearn 423). These “affective displays”, which have transformed users into habituated “smiley virtuosos”, are now fully embedded as vital data sources in the digital economy (Hearn 435).
Importantly, however, this does not exclusively concern well-known data collectors like the Facebook, Inc. corporation. Alongside the maturation of this social media ‘business model’ is an ongoing development of affective strategies in spaces that exceed the web in its purely digital dimensions. In addition to the platform user, the “user-citizen” now finds herself in a sensor-ridden “smart city”, connected to the net (Naafs; Van Dijck 206). The public sphere increasingly functions as a digitized sandbox for data extraction, and it is a sandbox whose operations remain relatively opaque insofar as governments and corporations do not allow full access to their collected data. As a result, users of public space may find themselves in situations where they are essentially “guinea pigs” in smart cities that have become infrastructural entities that function like a “black box” when it comes to data transparency (Naafs).
The rise of such data-mining techniques within public space has radical implications for our understanding of the social sphere, the nature of labour, and the relation between technology and its users. It also has implications for the methodology through which we understand those relations. The emoji, for example, is a clear input mechanism that is used to elicit and ultimately quantify what Stark and Crawford call “affective labor” (8). Users are asked to evaluate through a restricted palette of emoji, essentially an aesthetic manifestation of a streamlined data extraction strategy. To explore the dynamics of the social sphere as a sphere of production, consequently, it is necessary to closely examine this notion of affect, as well as its specific relation to labour.
In Politics of Affect, Brian Massumi defines the concept of affect as an interpretation of Spinoza’s essential understanding of the body as always capable of “affecting or being affected”. Affecting and being the subject of affect is always a conjoined event, Massumi explains, where acting upon another is only possible if you “[open] yourself up to being affected in return”. At its core, I believe, affect should then not be misunderstood as a synonym of everyday “emotions”, but as the bilateral arrangement of a body’s abilities at a given moment: a continuously changing configuration of embodiment, specifically in terms of the body’s interactive capabilities (Massumi 2; 3). At a foundational level, Stark and Crawford describe the term affective labour as being based on Sarah Ahmed’s theorisation of affect as “that what sticks” and makes connections between “ideas, values and object”. Thus, whereas the focus of traditional ideas of labour is on the ways in which human activity transforms and works upon material, an affective model of labour also focuses on the ways in which interacting with an object “moves us”: it has physical and psychological dimensions, so this “stickiness” of affect, to put it simply, is also a bodily event (Ahmed 32-33).
Additionally, Stark and Crawford link to Hochschild’s concept of “emotional labour,” specifically, explaining how “affective impulses” like digital smileys, but also “a flight attendant’s fixed smile” are currently vital “engines” for sustaining “social relations within the logics of economic instrumentalism and efficiency” (Ahmed 29; Stark and Crawford 8). When we approach these affective impulses from the concept of emotional labour, they may be understood to the extent of personal experience, or the “depth” of a person’s experience at that moment (Massumi 4). From the perspective of affective labour, however, I argue that we should also be concerned with the way in which personal experiences are not just receptive, but also responsive as part of an exchange; a bilateral relation of affect. In affective labour, social relations have become a capitalist building block, since economic value has shifted from “general” industrial labour towards “cognitive” labour; or in other words “communication put to work” (Lazzarato 85-86).
To clarify, here, both emotional and affective labour can be understood as specific perspectives on what Maurizio Lazzarato terms “immaterial labour”: truly a type of post-Fordist “living labor” that bases its mode of production on the human body: an “animated, mobile, intelligent, [and] reactive” source of value (Lazzarato 137; Berardi 21; emphasis added). The current post-industrial production cycle encapsulates more than just manual labour and strictly material commodities, like vacuum cleaners, computers or cars. Predominantly digital formats, like chat support, software, or blogs are now also
thoroughly absorbed into the global market. In the age of platform capitalism, as Nick Srnicek also explains, “cultural content, knowledge, affects, and services” have gained a central position, and the “product of work becomes immaterial” (38).
The idea of affective labour thus exceeds purely ‘online’ situations of liking or reacting on social networks. Whenever data is produced through affective responses, there is always an embodied individual involved, interacting with a systemic structure designed to extract quantifiable variables. By now, basic “social media logic”, like scrolling, liking or reacting, has consolidated itself as a new infrastructural “model for the sensor society,” where user activity is purposefully converted into data (Van Dijck and Poell 3; Andrejvic and Burdon 22). As cities are being equipped with feedback terminals and cameras that target and measure the public’s response, the concept and monetised logic of affect becomes more salient on an infrastructural level.
The question thus arises, how can we understand these ‘datafied’ settings in terms of their transformation of the body as an affective source of value? Can certain types of data-sensitive sensors be considered as more affectively ‘tuned’ than others? The use of emoji as a response mechanism has appeared in many airports, for example, where travellers are asked to rate staff performance. This ranges from customs officers to restroom attendants, as we will see in my first chapter, as Singapore Changi Airport has recently implemented a ‘toilet review’ screen system. Restroom visitors are asked to rate the toilet and are presented with a screen, or digital feedback terminal, that offers a selection of five different emojis, ranging from “Excellent”, “Good”, and “Average” to “Poor” and “Very Poor” (Fig. 1).
Other more ‘infrastructural’ examples in sensor society are exposure to Wi-Fi-tracking in public spaces (where a user’s store interest, loyalty and dwell time is logged), but also, to be discussed later in this thesis, interface moments with facial recognition software in transaction points in shops (Fig. 2) and facial detection software in digital advertisement screens at transport hubs (Fig. 3). The transaction points may require the customer to respond by smiling in order to confirm one’s online credit account and subsequent payment, while the digital advertisement screens opportunistically measure factors like the attention time, emotional response, gender, ethnicity, and age of passers-by that interface with the screen (Lee; Naafs; Verhagen).
Such uninhibited contexts of “evaluation” in affective labour processes, most obviously in the case of literal review screens, seem particularly compatible with Ahmed’s fundamental understanding of affect, as she explains in her text “Happy Objects”:
To be affected by something is to evaluate that thing. Evaluations are expressed in how bodies turn toward things. To give value to things is to shape what is near us (31).
Fig. 1 Toilet review screen at Singapore’s Changi International Airport (photo from personal archive).
According to Ahmed, the inherent aspect of being affected by objects is thus already a process of response and evaluation, which has been thoroughly adopted and translated into fairly straightforward, but also less conspicuous data-mining practices. A vital element that should never be overlooked is then the orientation of the body within an affective situation, since it plays an indispensable role in the production of value and social meaning. How is the body affected when it performs affective labour itself, as it becomes part of that bilateral exchange? Accordingly, how should one interpret the orientation of the body when it interfaces with urban screen technology in affective labour situations?
Interestingly, all of the infrastructural examples incorporate elements of user affect, shaped and facilitated by screen technologies like smartphones, review devices, and digital advertisements. These affective elements, inundated in a “politics of good feeling,” range from strategically presenting a selection of emoji, asking consumers about their feelings via a numeric rating, determining someone’s favourite stores, or monitoring what ‘kind’ of consumer smiles at which particular advertisement (Ahmed 30; Verhagen).
These forms of immaterial labour are also “immediately collective” as they only manifest within digital structures of “networks and flows” that are continuously converted into data-sets (Lazzarato 136). In these structures, an individual’s response is encapsulated within what Jodi Dean calls a “collective information and communication mesh through which affects and ideas circulate” (148). The valorisation of these affective responses within the capitalist system thus rests upon the conditioning of bodily orientation as labour, which is supported by infrastructural elements that incorporate both digital and material scaffolding.
In short, this is also a process of affecting and shaping the body. A person’s thoughts, feelings, and opinions have been rendered profitable by directing them towards specific forms or options of evaluation, a development that is heavily cultivated in the online realm (Terranova 103). As Deleuze theorised about emerging societies of control: the individual is steered into becoming a “dividual” as she is made ‘legible’ as data and interpreted in the midst of “masses, samples, and markets” (5).
Fig. 2 Example of the Alipay “Smile to Pay” transaction point (Wong).
Evidently, the rise of personal and public screen technologies in contemporary cities has a strong link to the rise of corporate media platforms with mass user bases. The two developments have recently converged to give rise to new digitized infrastructural settings in the material urban sphere, where “public affect” has become a “new standard
of value” (Hearn 429). The infrastructure of cities has become “platformized,” as Plantin et al. argue, and increasingly part of a “profit-driven corporate ecosystem” (3). Essentially, this corporate ecosystem is based on lucrative affective mechanisms, specifically functioning as a type of platformed “market discipline” (Hearn 423). Platformized infrastructure of course heavily relies on devices to elicit attention and source responses from mobile bodies (Berardi 105). As becomes clear, this does not just concern the smartphone, but also urban screens as proliferating sensors. These sensors now function as networked “checkpoints” that are “woven into the social landscape” of a city. Transaction points in supermarkets or restaurants, haptic feedback terminals at airports or customer service desks, facial detection software at train stations tracking advertisement demographics; all of these examples depend on “lurking” sensors that await our conscious or unconscious input.
Although individuals are not always forced to pass all of these checkpoints, nevertheless they are often still places of “passage” and “access,” like transport hubs or transaction points (Massumi 26). This network of checkpoints shape certain “functional paths,” as Franco Berardi terms them, that nudge the user or customer in a certain direction to render them “compatible” with the mode of value production (192). With the data they supply, affective labourers are primarily mobile and reactive “info-workers” that are continuously “reinserted into the global cycle of production” whenever they interact with networked, corporate devices (Berardi 90). In most cases, such devices incorporate an interactive screen with particular “technical and linguistic interfaces” that are designed to smoothly orientate the embodied user and facilitate data collection (Berardi 35). This leads me to my main research question: how do networked urban screens shape affective labour processes that enmesh the mobile and reactive body into the digital economy?
Fig 3 Exterion’s digital advertisement screens at a Dutch train station (Exterion Media).
Methodology
In order to contextualise my method of analysis, I will adopt Deleuze’s concept of societies of control and perform a “socio-technological study of the mechanisms of control” that involve affective strategies (7). In response to Massumi and Berardi’s assertions, I similarly understand urban screens as socially embedded checkpoints that often function as “coercive” moments of semi-voluntary “submission”, and think they should not be underestimated for their ability to carve and control the most profitable paths to exploit the mobile, affective labourer (Berardi 192). The way in which networked urban screen interfaces rely on the user’s “automatism of mental reactivity” should then also be examined more closely (Berardi 22). Consequently, I will perform close readings of three different affective labour settings, focussing on elements of the habituation of affective data extraction methods in digitized urban infrastructure, the asymmetrical social dynamics in data-based surveillance, and the precarity of the affective body’s position in the immaterial labour market.
The first screen-facilitated affective labour setting I will analyse is the toilet review screen at Singapore Changi Airport. The second setting is the “Smile to Pay” Alipay method, which was introduced as a form of payment through a facial recognition method in a KFC restaurant in Hangzhou, China. The third and final affective labour setting concerns digital advertisement screens by Exterion Media at Dutch trains stations, which incorporate small cameras at the top or side of the screen to monitor and collect data by
use of facial detection technology. Through these analyses, I will explore each affective labour setting in terms of how user affect is ‘converted’ into a profitable source of data. I will do so through several sub-questions.
Following Ahmed in her understanding that “the association between objects and affects is preserved through habit,” I ask how the habituation of social media logic (and other practices of framing through the screen) create tacitly naturalised conditions for such socio-technological settings (35). How do the specific agential dynamics between user, corporation and government interrelate and what are the social implications? Finally, incorporating Ahmed’s emphasis on bodily orientation in tandem with an exploration of how user affect is converted into data, a particular instance of the ‘dividual’; what kind of position is ultimately created for the individual’s mobile and reactive body in the digitized capitalist circuit?
Aim and Significance
In this ongoing development of affective labour strategies in the public sphere, a vital point of consideration is the position of the individual, customer, or “user-citizen” in our sensor-sensitive smart cities. User responses are elicited through affective strategies, where individuals often engage with screens without being made aware of the range of data they may be supplying. Data extraction strategies that monitor an increasingly passive “user”, including facial detection techniques in digital advertising screens, may be particularly problematic, where user consent does not even appear to play a role in the interactive dynamic. Hence, the overarching aim of this research project is to contribute to improved awareness and legibility for users in both active and passive affective labour settings. It also aims to improve our understanding of the body and embodiment in this process.
Our “cultural world,” which now certainly includes the digital, becomes implicit as a normalised “second nature” when it incorporates “procedures and rules designed to standardize behaviour” (Horst and Miller 28; Postman 141). It is exactly this rapidly standardized behaviour in affective labour settings that needs closer inspection. The habitual nature of expected behaviour in any setting, as Ahmed also points out, should not be taken for granted, particularly considering the way a “social context” is always a “controlling factor in how [we] behave” and shape the environment through our bodies (Postman 151).
Since this research project approaches the contemporary smart city as part of societies of control, I will include an examination of habituated data extraction methods
and social media logic. In terms of academic relevance, I intend to elucidate matters of subsequent “normative” communicative behaviour that is facilitated and shaped through urban screens. I will specifically do so by providing analysis that will further elucidate the question of how infrastructure is becoming digitally connected to platformized market mechanisms, responding to Plantin et al.’s initial exploration of this topic. There is a need for habituated market disciplines in digital settings to be incorporated in the socio-technological study of control mechanisms, certainly when it comes to the implicit extraction of human affect for profit (Horst and Miller 28).
II. The Toilet Review System at Changi Airport
The first chapter of my analysis of screen-facilitated affective labour settings will concern the toilet review screen at Singapore Changi Airport. The toilet review screens at Singapore Changi airport, no bigger than a regular tablet, consist of a sterile-looking, shiny white plastic casing and a colour touch screen. The screens are located on a wall near the bathroom exit, so that visitors are promptly presented with a small screen as they leave the area. “Good Evening “, the screen will say, “Please rate our toilet”. The screen presents the aforementioned text on a purple background, accompanied with a portrait photograph and name of the representative employee, in this case: “Chia Ah Moi” (Fig. 1). The logo of Singapore Changi airport floats in the upper right-hand corner, as to remind you which “brand” your toilet experience is associated with.
The lower half of the screen presents five emoji, a row of yellow humanoid orbs, and corresponding captions that describe the emoji’s intended meanings. The emoji’s captions range from “Excellent”, “Good”, and “Average” to “Poor” and “Very Poor”. The selection of depicted expressions varies from extremely smiley to decidedly sullen. Then, finally, at the bottom of the screen is a line of text that reads: “This screen is sanitised regularly”, possibly reminding the visitor of how dirty the screen may actually be, in a somewhat paradoxically reassuring manner. If the visitor responds by selecting one of the emoji, the screen will have successfully interpellated a response that is then recorded for subsequent data analysis and, in the case of complaints, to be immediately communicated to an overseer (Choudhury).
The toilet review screen, essentially a feedback terminal, is part of an overarching “E-inspection” system at Changi Airport (Choudhury). This system was introduced in 2010 and mainly functions as an instant feedback system where “maintenance staff report faults to contractors” and “airport users” can rate “counter staff, immigration officers, retailers and cleaners” (Xuan). By 2013, the Straits Times reported that the successful implementation of this digital inspection system had already “slashed maintenance costs by more than $2 million, improved response time for repairs by 30 percent and reduced manpower by 69, or about five per cent” (Xuan).
An interview from 2015, conducted with Changi Airport Group’s (CAG) chief information officer Steve Lee, revealed more about the company’s actual use of those
employee ratings, besides their role in cutting costs (Choudhury). In this interview, Lee explains CAG’s attraction to innovative technologies and links it to their ambition to become a “smart airport” as the “gateway to the smart nation”. Part of those innovations were the review screens, officially termed “Swift instant feedback devices” at “customer touch points”. In March 2015, there were 750 feedback devices in operation at Changi Airport. According to Lee, these screens have “streamlined workflows and processes” and “raised productivity levels of frontline staff such as washroom attendants…and other service personnel”. The main reason why the feedback devices have improved employee performance, Lee elaborates, is because the “immediate assessment of the service level provided by individual staff” helps supervisors to “command staff that show exemplary service”. Linking that to the benefits of the overall e-inspection system, Lee concludes:
Instant feedback empowers our airport partners, enabling them to be more responsive to our customers' feedback. The compiled ratings using business analytics allow our airport agencies to conduct monthly trend analyses and identify any service performance gaps for improvement.
Essentially, service employees like washroom attendants are therefore subject to the immediate surveillance and evaluation of an overseer, as well as the compiled, collective ratings that interchanging customers provide to CAG by responding to the review screens. Considering the relationship between affect and immaterial labour, CAG’s infrastructural absorption of customer feedback is then a typical example of “everyday movements and leisure activities” that are actively transformed into “surplus-value”. The lavatory visitor, a mobile and reactive body, is being capitalized upon through her voluntary evaluation of the most mundane daily activity that you might think of; a toilet stop (Massumi 28).
Digital Reputations and Asymmetrical Social Dynamics
From an initial perspective, the subjects that are involved in this particular case of a socio-technical control mechanism are the entity of the employer-corporation (CAG), the lavatory employee, and the lavatory visitor. The use of the toilet review screen is an important strategy on account of the employer-corporation, where “employers increasingly rely on a range of sensors to monitor workers”, such as “GPS devices that monitor drivers and delivery personnel, and even applications that track employees’ facial expressions” (Andrejevic and Burdon 22). This notion of surveillance through sensors corresponds to a
development where digital sensors, including such feedback terminals, are used to monitor employees.
This shift towards connected devices that supervise employees appears to correspond to Deleuze’s description of societies control as well, where society has moved from the labour conditions in the traditional factory towards modern-day corporations that “operate with machines of a third type, computers” (6). The lavatory visitor that actively responds to the screen thus cooperates with this type of surveillance, which is ultimately a control mechanism meant to keep employees and their behaviour in check. In this case, the use of monitoring software makes primary use of emoji to elicit a user response, which intends to “extract data from [users] more efficiently” (Stark and Crawford 8). The user who responds is subsequently entering into an interaction that constitutes a form of “affective expression” as immaterial or “free labour” (Hearn 434). By responsively engaging with the emoji as social buttons that operate on a familiar social media logic, visitors become users that “voluntarily engage in productive activities without financial reward” in such “affective economies” (Gerlitz and Helmond 1316; Van Dijck and Poell 3; Rey 413).
Controlling the behaviour of the employee now functions through an “outsourcing” of labour, moving from a traditional supervisor in disciplinary society to a distributed, mobile type of surveillance through free labour in societies of control (Hearn 435). Whereas the workplace was previously regulated by “the boss who surveyed each element within the mass”, the mass or collective now takes turns to survey itself (Deleuze 5). Fundamentally, selecting one of the options is here also an act that recognises the “affective conditioning” of reacting to a certain situation through the use of emojis (Hearn 423). This surveillance strategy evidently uses a type of affective communication that is sufficiently familiar for me and you to know how to respond, reminiscent of the type of “reacting” we see on social media platforms like Facebook.
On a larger scale, the user input of the lavatory visitor also contributes to a type of “digital reputation” that is assigned to the employee (Hearn 434). The collective labour of the lavatory visitors giving feedback is then communicated to the employer. This communicated data-set produced by multiple visitors ultimately shapes the employee’s digital reputation. It is quite clear, however, that this reputation is not produced outside of hierarchal power structures. The response data is also a form of information that “inevitably exceeds the control of those individuals who generate it or the individual who must ‘carry’ it” (Hearn 424). This is not an informal setting or “neutral channel for data
transmission” where networked Facebook friends reciprocally react to each other’s posts (Van Dijck and Poell 10). The lavatory employee is clearly not an online friend, she is providing a service to the visitor, consumer, and reviewer.
The toilet review screen at Singapore Changi Airport is not a case of an active self-representation through digital reputation, but rather a case of the lavatory employee being ‘subjected to’ a reputation” (Hearn 424). This reputation is both enabled by how the corporation-employer has arranged the lavatory setting and placed the screen, as well as the way in which visitors agree to respond to this interpellation to review the employee’s job performance. These hierarchically-structured, asymmetrical power relations between subjects are clearly shaped through interactive engagement with the toilet review screen, which elucidates the object’s theoretical potential and consolidates its central position in my analysis of a “networked data-driven ecology” (Van Dijck and Poell 11).
The Habituation of Social Media Logic
In order to better understand the underlying social dynamics that enable the toilet review screen to successfully elicit a response, the familiarity with the activity of reacting to something by selecting pre-defined emoji options deserves further attention. This requires a closer consideration of the way in which social media logic and “digital reputation economy” play vital parts in our affective conditioning, which I essentially identify as an evident form of market discipline (Hearn 423). As I stressed before, it is important to realise how the toilet review situation should not be easily conflated with reciprocal interaction between online friends on social networks. Still, it is clear that the internet and social media logic have become a model for the sensor society, especially the ways in which interactions and “movement through cyberspace” reliably produces “data that can be collected, stored, and sorted” (Andrejvic and Burdon 22).
In its earlier stages, the digital realm was an experimental breeding ground for emerging activities that were “not immediately recognized” as “free cultural/affective labor”, like creating fan sites, posting product reviews on YouTube, or sharing an insightful article with your Facebook friends (Terranova 103). Today, it is no secret that much of our activity on social networks functions as ‘free’ publicity for whatever we are liking, sharing, reviewing, or rating. Moreover, that activity is stored and converted to meaningful data to be sold for commercial purposes. In fact, these exact affective displays of ranking and rating have become “moment[s] of experiential re-structuring”, where the input data is processed to become “profitable information” (Hearn 423). This means that
reaction through emoji is a streamlined input mechanism that enables social behaviour and simultaneously produces easily navigable data-sets. In short, the emoji as input mechanism has become a “means to quantify, measure, signal, and control affective labor” (Stark and Crawford 8).
This ‘evolution’ of social media logic to other places and parts of life continues to blur the differences between “human connections and commercially and technologically steered activities” (Van Dijck and Poell 9). If we let go of our conception of labour between “four walls” and our outdated “factoryist prejudices”, as Lazzarato describes it, the “cycle of production of immaterial labour” becomes immediately more perceptible (136). It is clear that our continuously encouraged affective displays do “contribute to value generation”, but not quite “for the person doing the ranking and the feeding back” (Hearn 435). Indeed, as is the case with the toilet review screen. The decision to supply feedback, this form of affective labour, fails to provide any substantial reward to the lavatory visitor, except the promise of more ‘streamlined’ services.
The way in which the lavatory visitor gains influence as a social agent is how the visitor agrees to become complicit in monitoring and ultimately controlling the toilet lady’s behaviour. Regardless of whether the visitor did so consciously or not, by responding to the review screen, the public agrees to adopt the outsourced role of a collective surveiller and data producer. Evidently, matters of habituation and subsequent “normativity” of behaviour in digitally mediated social settings need to be incorporated in a socio-technological study of the mechanisms of control, especially in relation to implicit immaterial labour (Horst and Miller 28). Arguably, the use of emoji as an affective strategy to elicit a review of a toilet experience is in itself not a particularly astonishing feat or innovation. Instead, I find the apparent ease and speed with which we collectively create and implicitly understand “normative conditions for their use” a more relevant topic of inquiry (Horst and Miller 28). Apparently, the review screens all around Singapore Changi almost seamlessly fit into existing cultural conventions of controlled behaviour.
Noticeably, the screen itself is also subject to regular hygienic checks and needs to be controlled in its own right, monitored and cleaned for its ability to spread potential pathogens. Reading this tiny notice at the bottom of the review screen again reveals how current structures of surveillance within societies of control are certainly not a given or natural state of things; they are, as Deleuze also traces, the result of the development from disciplinary regimes (as described by Foucault) to an ongoing shift to societies of control (3). Spaces are meticulously organised in order to be optimally controlled and to evoke the
desired habitual response, functioning eerily similar to a kind of “biological immune system” (Postman 72-73). Of course, these mechanisms of control do not only literally concern matters of hygiene, but also metaphorically concern potentially unwanted and uncontrollable behaviour of employees. In this immune system analogy for “social institutions of all kinds”, which I am borrowing from Postman, the aim is always to avoid the risks of “information chaos”, where human behaviour (analogous to uncontrolled cell growth) becomes unpredictable or unwanted (Postman 73). In order to maintain a cost-effective environment like CAG’s e-inspection system, where people are meticulously directed to supply the desired type of information, the pre-determined “standards of [information] admission” are rigorously defined.
For the specific case of the toilet review screen, the restricted palette of emoji responses would then be the standard of admission; a streamlined data extraction strategy that pre-emptively shapes the types of information that visitors can submit; the types that are, naturally, also most useful and lucrative to the corporation. CAG’s spatial strategy of eliciting a response from and directing the behaviour of lavatory visitors is then indirectly a method to control the behaviour of their employees. It is precisely the orchestrated structure of screen-facilitated interaction between the lavatory visitor and employee that enables the employer-corporation to direct behaviour within these spatial settings. To subsequently avoid the disorderly complications of “information on the loose”, institutions will often limit and “[deny] people access to information” (Postman 72-73). Neither the respondents to the screen or the lavatory employee (recipient of the consequences of that response), have full or partial access to the data that constructs the employee’s digital reputation. The respondents have no insight into the effects of their actions, and the lavatory employee has no choice but to shoulder whatever consequences the aggregated responses may bring along.
Further analysis thus exposes how the cultural world can only function as a normalised “second nature” when it communicates “procedures and rules designed to standardize behaviour” (Horst and Miller 28; Postman 141). Socio-technical objects like the toilet review screen are most certainly imbedded into this assemblage of control, whose infrastructure might affect the lavatory employee’s behaviour as much as it shapes the visitor’s actions: it shapes our functional paths (Berardi 192). It is this realisation of interconnections between spatial settings and normalised behaviour that has prompted digital anthropologists like DeNicola to reassert how “digital culture remains thoroughly socialised and materially entangled with spatial experience” (83).
It is indeed through a “conjuncture of the material with the socialization of habit” that the visitor knows how to interact with the toilet review screen, almost mechanically performs an immaterial act of labour, and willingly adopts the expected role within an environment of control (Horst and Miller 28). As cognitive workers, whose communicational minds are strategically moulded, we should remain conscious of how our interactions are guided by spatial settings and semiotic cues. The inherent “plasticity” of our brains makes our minds extremely sensitive to the shaping effects of material and digital architectures, Catherine Malabou warns, as we are essentially neuronal “sculptures” ourselves (7). The preservation of certain associations between objects and affect depends on habit, repetition, and routine (Ahmed 35). We are inherently susceptible to methods of socialisation that can significantly influence our behavioural patterns, often without being fully aware of the process. Naturally, these underlying mechanics of the seemingly naturalised cultural world become ever more unconsciously experienced as digital technology continues to develop (Miller and Horst 25).
The Bodily Matter of Affective Labour
Following the understanding that the naturalised cultural world implicitly guides the public’s behaviour, we should not allow the digital and immaterial nature of socio-technological activities elicited by networked devices like the toilet review screen to obscure the fact that social relations of control always involve material bodies. Considering the shift towards digital settings, as emphasized by DeNicola, it has never been more crucial that we understand how “human bodies themselves are incorporated as nodes within a network, normativizing constant surveillance” (83). It has now become clear how both the bodies of the visitor and employee are vital nodes within a strategically guided network of social relations and interlinked value production.
Immaterial labour, in this case a type of affective response to review the lavatory employee’s job performance, is truly material to the core. The question is not so much whether the visitor’s choice to touch that emoji button counts as a ‘real’ or material social interaction. Essentially, it would be fair to argue that one does not technically communicate with an actual person, but is only touching a (presumably) bacteria-ridden plastic surface. However, as Miller and Horst specify: “the critical feature of digital technologies here is not [strictly] technical; it is the degree to which they impact upon power” (27). In affective labour settings, the act of communication is always modified into a capital relation, and there are those profit in excess (Lazzarato 142). The interaction
literally and figuratively “comes to matter”, as it produces material consequences for the lavatory employee’s workplace experience, as well as her job security.
The mass activity of reviewing, rating, and ultimately grading a person’s job performance, however superficially mediated it may seem from an individual perspective, most definitely has a collective influence on a human body and, ultimately, the employee’s quality of life. Primarily, providing feedback is an act of internalised compliance to the surveillance of others, but it is also a form of self-exploitation. When lavatory visitors respond to the review screen, they follow a pre-determined, functional path and readily enter a systemic configuration that is designed to extract surplus value from a seemingly trivial social interaction.
In the case of the toilet review screens, the system undoubtedly utilises a “numerical language of control” that consists of codes that either “mark access to information, or reject it” (Deleuze 5). This inherently implies asymmetrical social dynamics concerning the use of data and value production, which is a precarious matter. As capitalist communicational relationships between producer and consumer, the customer (in this case the lavatory visitor) becomes a “simple relayer of codification and decodification, whose transmitted messages must be ‘clear and free of ambiguity’”. This is achieved by implementing a system of networked devices that encourages visitors to respond via pre-defined emoji, which creates a “communications context that has been completely normalized by management” (Lazzarato 134-135). The act of evaluation, even if there is no substantial reason or reward for anyone to comply, has been purposefully normalised as an expected type of behaviour within corporate environments.
We should remain critical of what Jodi Dean names the circuit of “communicative capitalism”, in which affective labour settings are infrastructurally integrated, since it “celebrates” those “injunctions to participate, to express, to be part of a common”. The problem with this type of collective ‘participation’ through evaluation and digital reputations, however, is the way in which this “common” is “expropriated” rather than “shared” (Dean 162). We do not collectively benefit from the data we voluntarily supply, it serves a select group of people that profit. It is thus vital to strive for a conscious understanding of the cultural mechanics at play in order to properly assess one’s own influence and responsibility as part of a corporate environments of control.
As P.J. Rey accordingly forewarns in relation to the exploitative threat of immaterial labour: “If people are ignorant of, or unconcerned with, the value they create for companies, exploitation becomes only more insidious. And, wherever exploitation
exists, social inequality follows in its wake” (416). Data sets that underly digital reputations can only exist in the collective, within a network of relations and interactions that assign and generate value. These are transactional interactions, where the communicative action of two parties, the lavatory visitor and employee, affect each other. At a superficial level, it appears as though the employee is simply expected to perform a satisfactory service to the visitor, and the visitor reciprocally expresses their opinion about the quality of that service. Yet, the implicit third party, the corporation-employer who enables this template of transaction, is ultimately the only body that gains.
Directed by the review screen as a networked checkpoint, the lavatory visitor is enmeshed into the spatial template as a mobile and reactive body that is socially coaxed to fulfil a functional role. The lavatory employee is enmeshed within the same template, but is rendered passive rather than reactive. She is on the receiving end of the visitor’s response, much less mobile and rather serving a cornerstone position within this socio-spatial template of obfuscated data production. In this process of evaluation, both the visitor and employee are purposefully orientated towards a performance of affective labour, and both are made to be numerically legible. Subjectivity is only taken into account so it may be “[codified] in line with the requirements of production” (Lazzarato 135). The visitor’s affective response is pre-emptively shaped by the screen’s limited input mechanism and instantly made legible to the system. This response is then absorbed into a data set that continually morphs into the employee’s imposed digital reputation. Above all, this bilateral enmeshment of social relations is part of a larger, asymmetrical process that produces corporate subjugation on the basis of affect, and specifically affect as a source of surplus value.
III. Smile to Pay and the Sesame Credit System
In the second chapter of my analysis of screen-facilitated affective labour settings, I will continue to examine the emergence of digital reputation economies and their subsequent influence on the body, as well as the body’s role in their production as part of the capitalist circuit.
Although it remains the main focus of my analysis, it is important to realise that the enmeshment of the body within the capitalist circuit is not strictly limited to its affective responses. With emerging biometric technologies like iris scans and voice recognition, it is clear that concepts of citizenship and identity are gradually becoming more closely linked to the identifiable, biological body. Where we previously secured citizenship through abstract numbers, like social security numbers or passwords, states increasingly prefer using biometric information as a more trustworthy resource. In relation to the topic of government surveillance in societies of control, this can be seen as a clear instance of the rise of the “individual body” as a “mobile pass-code” as Kirsty Best has phrased it (14).
The use of biometric methods, however, is not isolated to official documents and governmental mechanisms. Across various contemporary societies, biometric technologies are currently being introduced into a “scanscape” of corporate settings, more specifically as methods of payment (Best 11). One example of the body as payment method is the “finger vein ID” in British Barclays and Costcutter supermarkets, which utilises infra-red technology to register and read a person’s unique vein pattern (Collinson; Morley). This method is preferred to the ‘regular’ fingerprint, since reading a vein pattern requires a living finger, whereas fingerprints can still be read off of a “cut-off finger” (Collinson).
Another example of the body as payment method can be found in Hangzhou, China. In 2017, Alipay introduced its “Smile to Pay” method at a KPRO restaurant, a ‘healthier’ version of KFC. By use of sophisticated facial recognition (3D cameras and likeness detection algorithms), customers authenticate their payment by smiling, a simple affective performance that confirms the presence of a living person (Lee). The customer will then be asked for his or her phone number as a final verification, as to confirm the customer’s Alipay account, which is, in turn, linked to a customer’s identity as a resident of China.
For both these payment methods, a particular body part carries the central focus (the finger or the face), but the transactions depend on the body being whole and living; a fully embodied individual. Yet, out of the two methods, the case of Alipay’s smiling method becomes particularly noteworthy when placed in a larger framework of data collection systems, revealing political dynamics on a national scale. Tech giant Alibaba Group, the establishers of Alipay, has namely been selected by the state-owned People’s Bank of China to develop a pilot programme for assigning credit scores to consumers, on a scale anywhere between 350 and 950 (Hornby)1.
This form of government sponsorship was not a random decision, since China has plans to develop a nationwide “social credit system” for all its citizens. Alipay’s reward-based “Sesame Credit” service, where high scores offer access to certain goods and privileges, is only one of many provincial-level pilot programs (Ming). The nationwide version is envisaged to offer a comprehensive ‘score’ for every adult citizen by 2020, based on various factors like financial credibility, criminal record, and social media behaviour (Obbema et al.). This would instantiate a state-monitored digital reputation that determines accessibility to certain jobs or housing, for example (Hearn 434; Obbema et al.). Consequently, digital profiles of citizens as dividuals, gathered amidst the “masses, samples, data, markets, or banks,” will do more than create scattered “simulations of the original” (Deleuze 5; Best 10). These digital reputation profiles of user-citizens quite literally quantify the body and control citizen agency through a “score” (Amoore 27; Van Dijck 206).
By valuing its citizens through a numeric language of control in a reward-based system, it seems that China eventually aims to nudge its citizens into a very specific direction, an incredibly ambitious outline of a functional path. The ultimate aim is for the population to self-discipline their behaviour and fit into a mould of an ideal responsible citizen to the state. This is where Alipay and its Smile to Pay method sets itself apart from other ‘novelty’ payment settings like the supermarket finger vein ID, which are usually exclusively managed by private corporations. In the British supermarket, the boundaries between your ‘dividuality’ as a consumer and citizen an sich are significantly less blurry as compared to Sesame Credit.
1 The Sesame Credit system by Alibaba Goup’s Ant Financial is only one of eight pilot programmes
that have been selected by the People’s Bank in China in 2015 to test credit scores for consumers. At this point in time, the participating companies “operate their own e-commerce and online financing arms” and do not share their data with the other rival platforms. This means there is currently no true “comprehensive score” just yet (Hornby).
What I thus find most intriguing about the Smile to Pay payment method here, is how it only appears to be one particular architectural instance, again a networked checkpoint, that belongs to a much larger system of consumer-citizen surveillance. With its production of digital reputations, it is a system that targets the data-based construction of an individual identity that ultimately implicates the user’s body. The individual that is expected to embody this identity as a “data derivative”, however, is derived from a wide range of data collection moments, which Louise Amoore calls an “amalgam of disaggregated data”, and essentially an act of “inferring across the gaps” (27).
What happens when this multitude of derived simulations are collectively attributed to the embodied individual in the form of a numeric score? The integration of biometric technology, which initially inspired a shift of attention to the body, could be interpreted as a ‘direct’ and even frontal form of enmeshing the body as information. However, from a more ‘zoomed-out’ and increasingly oblique perspective, the body seems to be more insidiously ensnared into the world of data than ever before: the multitude of data collection moments that span across digital platforms and material infrastructure cumulates in an abstracted numeric score that marks values of trustworthiness onto the citizen (Botsman; Massumi).
Fig. 5 Examples of app interfaces that display Sesame Credit scores (Huang).
The Pentagram of Networked Citizenship
Unfortunately, because Alipay has never made its algorithms public (Ming), the exact method of calculation behind the Sesame Credit score cannot be assessed in this research project. From the user’s end, however, the workings behind Sesame Credit are still somewhat accessible for contemplation. This can be done by viewing a diagram of the score itself across the platforms that integrate Sesame Credit. This diagram is shaped like a pentagram and shows how the user scores on five different factors of assessment. The five different factors are described as “credit history”, “behaviour and preference”, “fulfilment capacity”, “identity characteristics”, and “social connections” (Li). Importantly, it should be noted that the results in the scoring pentagram have already been processed before they reach the user, and they tell us little about their underlying criteria. Still, the five factors might partially reveal undisclosed ideas about what ‘kind’ of user deserves to receive a successful score within the Sesame Credit system.
The calculation of credit history reportedly includes monitorisation of credit card repayment, as well as personal ratings that the user may hold on Alipay-compatible
e-commerce websites like Taobao. The behaviour and preference section seems to account for online activity in the broadest sense, such as which websites the user visits most, which products are purchased, and which consumer segment(s) the user belongs to. The ‘type’ of websites and products would then influence the user’s rating in terms of responsible behaviour. Which exact websites and products increase a user’s score has never been fully explained, but Sesame’s Technology Director Li Yingyun has previously offered an example, explaining that: “Someone who plays video games for ten hours a day” would be considered “idle”, whereas somebody who “frequently buys diapers would be considered as probably a parent,…more likely to have a sense of responsibility” (Botsman). The fulfilment capacity factor is said to incorporate data on the user’s ongoing financial products (like loans), the user’s periodic social insurance payment of i.e. residence and vehicles ownership, and the user’s Alipay account balance. The identity characteristics factor, reportedly rated on “accuracy,” incorporates the user’s address, period of residency, employment, education, and phone numbers, which can be imported from external platforms like LinkedIn (Li).
Lastly, yet perhaps most importantly, the social connections factor rates the user’s activity and influence within social networks, and includes the credit scores of the user’s friends. Friends with lower scores will be detrimental to one’s own score, which should encourage users to interact with other users that are considered ‘trustworthy’ (Huang; Li). Subordinating friendship to the reputation economy would then fully instrumentalise the social relation as a capitalist building block. If the exchange of affect is the process that sustains such social relations, (reciprocal) affect becomes the most critical strategic asset in forging mutually beneficial reputations and sustaining privileges. Interactions in both private and public spheres, if they can even be seen as separate anymore, must then be held to a certain standard of what may count as desirable networked citizenship.
Consequently, it seems more than likely that such hierarchal dynamics will lead to isolation for individuals with lower scores, as well as certain ‘classes’ of citizens that may only want to interact with each other or individuals with better reputations. When there are structures in place that force “individuals to correspond, without gap or contrast, to their digital traces”, one can anticipate the formation of “new social stratifications” in segmented groups of citizenship (Reigeluth 251). Naturally, this system ultimately strengthens the government’s ambition to mould its citizens into well-behaved members of society. For example, when a social media user shares content which Sesame Credit assesses as carrying “positive energy,” that user’s score will regularly go up. This positive
energy content can be in the form of compliments about the government, or expressions that emphasize “how well the country’s economy is doing” (Botsman). If a friend or acquaintance shares such a positive post, interacting with that content in an affirmative manner will then presumably have an advantageous effect on one’s score as well. In principle, the digital reputation is thus a pedagogical government tool that thrives on the fulfilment of pre-approved interactions within the crowd, a system that aims to continuously “[feed] back into the loops of the individual’s self-control” (Reigeluth 251).
Sesame Credit as a Dataveillance System
Similar to Van Dijck’s idea of “data as currency”, users comply with the “trade-off” of personal metadata for access to platform services like Alipay and Sesame Credit (198). The incentive to participate in the Sesame Credit system is simple convenience, but also a range of benefits or rewards for users. Examples of such benefits are easier access to loans, ‘getting ahead’ on job-seeking websites, easier access to travel visas (available for users with scores over 700), easier access to car rental services, booking hotel rooms without a paying a reservation fee or deposit, access to a VIP dating profile on the dating website Baihe.com, borrowing privileges at a local library, free loaner umbrellas, and free lottery tickets (Li; Ming; Botsman). Evidently, this wide range of benefits covers principal aspects of citizenship (like mobility and financial status), but also seemingly ‘playful’ aspects like watching videos or entering a lottery.
Sesame Credit is thus a system “not only of rewards, such as…the accumulation of loyalty points,” but also a system of detriment or even “punishment” (Best 17). For example, those who opt out will experience a more scrutinized security check at the airport or hold a comparatively disadvantaged position when applying for jobs. This further consolidates Sesame Credit as a socio-technological system within a control society that increasingly self-disciplines through “participatory” surveillance (Best 17). According to Rogier Creemers, a researcher of Chinese law at Leiden University, punishment measures already go beyond mere disadvantages for opting out. In the case where a user with a poor score commits a traffic violation, for example, the citizen may be classified as a “trust-breaker.” Such a status can lead to penalties on things like “career progression” and “asset ownership”. Bearers of low credit scores that fail to repay debts may even be put under restrictions and cannot legally use air travel (Ming). Given the growing and envisaged ubiquity of the platform on a national-wide level – and the fact that opting out is not such a straightforward option anymore, the idea of self-discipline may even prove to be become
meaningless. Instead, a system that leverages privileges and punishments rather operates coercively to mould an individual in the image of its own capture of affect as transaction. Again, the crowd is neuronally sculpted to comply with an envisaged model of the ideal cognitive worker.
Considering the incredible scope of user activities that are integrated in Sesame Credit’s production of personal scores, however, the question of surveillance certainly seems to be one that rather heads toward Van Dijck’s formulation of dataveillance: “the monitoring of citizens on the basis of their online data…, [which] entails the continuous tracking of (meta)data for unstated preset purposes” (205). It is not quite the case that citizens are temporarily subjected to surveillance for a delineated purpose, like a suspect in a criminal case would be. Instead, every activity that can possibly be tracked is pre-emptively mined to be incorporated into myriad of algorithms. These algorithms subsequently produce a continuously shifting score that a user may be positively or negatively affected by in everyday scenarios.
Van Dijck further characterises dataveillance as an increasingly widespread method for “monitoring citizens through social media and online communication technologies” and emphasises that ideas of “trust and belief” are particularly vital for user-citizens to participate in the system and “have faith in the institutions that handle their (meta)data” (198; 204). In the case of the Sesame Credit score, simultaneously “financial credibility indicator” and “compliance mechanism,” the system aims to reward citizen-consumers that are deemed trustworthy to elicit participation (Ming). This is in itself dependent on the citizen-consumer’s trust that even if behaviour is not 100% accurately measured, participating in the system will still somewhat adequately and consistently lead to benefits for the user.
The Spatial Body in a Data-Sensitive Environment
Having examined how Sesame Credit operates as a socio-technological system of control that primarily depends on methods of dataveillance, I will now shift the attention back to the body, and specifically the body in its spatial qualities. Knowing that the Sesame Credit score is generated across a broad range of monitored activities, it is especially interesting to see how the body as “mobile pass-code” serves as a benchmark against which these activities are continuously measured and interpreted. As Best explains, the individual becomes the new, mobile “site of surveillance” (14). Similar to Amoore’s data derivative, the Sesame Credit user is indeed a “body in movement” that leaves dispersed traces (36).
Still, there is a discrepancy in the way in which Amoore conceptualises this fluctuating data derivate and the way that Sesame Credit actually uses data to interpret and construct a subject. Whereas Amoore emphasises how the mobile data-mined subject is always held to a (algorithmically-sensitive) changing norm and therefore incompatible with categories of “this customer” or “that visa applicant,” the Sesame Credit score is explicitly aimed at identifying and attaching multiple of such dividual ‘profiles’ to a single citizen and their body. This body as pass-code subsequently serves as a simple verification method in settings like the Smile to Pay payment method, but more importantly as a physical carrier of whatever privileges or disadvantages one’s data profile generate in daily life. Data surveillance manifests its influence in the interplay between the body and infrastructure. So, where should we place Sesame Credit’s embodied dividual in the analysis of data-sensitive architecture, particularly considering the current “scanscape” and its countless interface moments (Amoore 39; Best 6)?
The individual with a high or low Sesame Credit score, which is instantiated through a algorithmic ‘summation’ of dividual manifestations, is clearly more than a silly statistic. It is not only a matter of digital reputation amongst friends and acquaintances. The corporate-governmental agency of the state and Alibaba Group has direct effects on the body of the citizen. The credit score ultimately determines which bodies acquire privileged or precarious positions in various settings. The score influences if and how easily bodies can pass through spaces when travelling, or who can go up or down professional ladders. On dating websites, the score determines which bodies should count as desirable life partners, and who deserves a partner the most2.
In order to understand how a digital reputation can have such far-reaching effects, it may be useful to understand Sesame Credit as part of a larger development that entails the infrastructuralization of platforms. Plantin et al. explain this development as the way in which “media environments increasingly essential to our daily lives (infrastructures) are dominated by corporate entities (platforms)” (3). This surely seems to fit the case of Sesame Credit as a pilot programme that ultimately envisages comprehensive dataveilled control of Chinese citizenship by 2020, whether that concerns mundane library visits or major loan applications. Alibaba Group’s control over programmes like Sesame Credit, but also the proliferation of Alipay in e-commerce networks seems characteristic of this platform infrastructuralization, considering how it is “embedding itself” into the
2 Here I am referring back to the examples of rewards and benefits I discussed earlier in the paper (i.e.
users with high Sesame credit scores have access to faster visa application and VIP dating profiles on Baihe.com).
background of “daily existence” as “seamlessly interconnected systems and services” (Plantin et. al 12).
Paying for a roasted chicken meal at KPRO, for example, certainly seems to fit that bill. The embodied dividual becomes spatially integrated within a data-sensitive environment of platformized infrastructure, quite literally through contemporary methods of biometric technology in the Smile to Pay example, though more imminently as the physical and mobile carrier of a digital reputation. New media features may challenge the idea of “bounded and contained bodies”, but in order to understand the dividual in control society, embodiment cannot simply be ignored (White 615). Even as we accept the idea of “multiple, lagging, fragmented, folded, divergent, and extended selves” that are produced in a networked landscape of masses of data transactions, we should not forget that human bodies are always vital nodes within a network of constant surveillance (DeNicola 83). Here, the body as ‘node’ is an embodied dividual within a digital reputation system, subjected to privileges and mobility, but also discipline and (the threat of) punishment.
The Affective Body in Sesame’s Digital Reputation Economy
There is more to be said about Sesame Credit’s data-generated digital reputation, especially in relation to its affective dimensions. Plantin et al. also explain how the platformization of infrastructure contributes to the “conflation” of “economic logics typical of platforms with public interests and quasi-universal services” (14). This is a particularly relevant observation in the case of Sesame Credit’s entanglement with governmental forces, where the state sponsors a corporation that specialises in e-commerce to evaluate factors like political inclination and financial responsibility. Such entangled relations also resonate with Best’s observation of problematic disciplinary mechanisms of both “corporate and state bodies,” where they construct “data subjects for the purposes of both commodification and surveillance.” This leads to a position of “relentless” data extraction, Best argues, for anyone who desires to “participate in almost any form of citizenship or consumption” (8).
Often, these economic logics of social media and e-commerce platforms have increasingly depended on user affect to generate data profiles. Once again, this kind of user affect in the digital reputation economy is based on feelings and opinions and other affective displays that citizens are required to display as “smiley virtuosos” every day (Hearn 435). For the Sesame Credit system, clear examples of this affective logic are found in the promise of credit points after writing, sharing, or reacting to “nice positive energy”
content about the government and economy, but also in the form of continuously smiling to confirm your own embodiment as a method of transaction. Within the Sesame Credit system, user affect thus becomes valued as a new form of currency; credit points that will potentially improve your digital reputation (Hearn 422).
Still, the integration of users’ affective impulses as powerful “engines” that support the logics of economic instrumentalism goes much further than just niceness and smileys. The “social relation” in the broadest sense forms the basis of platformized economic logics, which is already fundamentally apparent in a score that measures reputation and attributes privileges accordingly (Stark and Crawford 8). Reputation is only relevant in a world where social relations determine how the individual is emotionally valued by others. This becomes even more salient when considering the fact that the scores of the users’ friends influence the users’ own score. This coding of social life was only possible with the rise of the Web 2.0 and social network sites, Van Dijck argues, where the dividual’s “friendships, interests, casual conversations, information searches, expressions of tastes, [and] emotional responses”, which all depend on the affective body as a social conduit, became legible as (lucrative) data sets (Van Dijck 198). If we read affect as the “process by which emotions become embodied,” and users reap rewards when they perform ‘nice’ and responsibile citizenship, the type of citizen that is thus promoted and affectively conditioned is that of the “transactional ‘self’”, where users “perpetually groom” a “bestselling ‘self’” (Rosler 1;2).
In the case of Sesame Credit, this bestselling self (a product of the digital reputation economy), becomes most apparent in contexts of using the score as a public asset for matchmaking websites like Baihe.com. Here, the credit score is meant to serve as a verification method for displaying your reputation as a responsible citizen, and implicitly a ‘good person’ and reliable life partner (Botsman). Simultaneously, one can imagine how users with lower scores might feel apprehensive and disadvantaged on such reputation-based social platforms. In terms of the affective body as an economical asset, what could be more important than the ‘transaction’ of love between two (equally) ‘trustworthy’ citizens?
Ant Fortune, a branch of Alibaba Group, has recently made this message exceptionally clear by posting these advertisements for Sesame Credit on Weibo.com (figure 6 and 7).
