This is a pre-print of Carrigan, M. (2018). The evisceration of the human under digital capitalism. In Realist Responses to Post-Human Society: Ex Machina (pp. 165-181). Routledge. Please see the final version if you want to cite this.
The case of social media data illustrates why this reduction is problematic but the point is a broader one: the orthodox framing of transactional data reduces action to behaviour, obscuring swathes of meaningful human activity and failing to account for the role of infrastructure in shaping it. Resisting the dissolution of the former into the latter does not entail a denial of behaviour as a relevant factor in understanding (digitalised) social life. Not all action is social action, despite a growing theoretical tendency to assume this is the case (Archer 2000, Campbell 1998). Furthermore, some of the most sociologically interesting and politically pertinent features of digital capitalism involve the deliberate attempt to intervene and manipulate at the level of behaviour (Davies 2015). But this dominant framing of ‘big data’ obscures the role of the human in social digitalisation, forming a crucial part of a powerful cultural movement towards the ‘evisceration of the human’: treating individuals as if they lacked reflexivity, being passively susceptible to behavioural interventions, rather than as active contributors to a profound transformation of social life (Couldry and Hepp 2016).
For all the excitement attached to the ‘flood of data’ and the possibilities it offers for a resurgent naturalism in the social science, there is nothing inherent to transactional data which demands a behaviouristic interpretation (Conte 2012). There is an ideological supplement at work here, a cultural project to overcome the irreducible ambiguities of the hermeneutic dimension to social life, driven by the belief that digital data enables us to see ‘who we are when we think no one’s looking’ and a commitment to a ‘utopia of total social legibility’ (Couldry 2015, Little 2015, Rudder 2015). The intellectual commitments we can find amongst designers, engineers and scientists across academia, government and commerce exercise a real influence over human action: the categories of their thought are coded into now ubiquitous systems for mediating social life, proving real in their consequences if not accurate in their descriptions. ‘Big data’ evangelism should be treated as a cultural form, reflecting a belief that the ‘book of the social’ can be read in the same way as the ‘book of nature’ has been, with all this entails for the status and reality of the now mathematicised human being (Barnes and Wilson 2014).
The Politics of Transactional Data
The scope of digitalisation inevitably poses questions which are best described as political, in the sense of struggles over the recognition of interests and distribution of resources. Much as with the other dimensions of transactional data considered in this chapter, its politics is manifest across a dizzying array of fields that easily lends itself to a focus on individual cases without attempting to draw out their commonalities. Undertaking ontological analysis is helpful in relation to such a multifaceted phenomenon because it allows us to (fallibly) identify mechanisms which are operative across a wide range of empirical cases. This is important because the functionality we can empirically discern could always manifest itself in different ways, with its mode of implementation reflecting features of the prior context rather than something intrinsic to the technology itself. In fact, the notion of ‘big data’ can serve as a smoke screen, providing a discursive capacity to make an epochal cut (“this is how we do things now”) which forecloses the other social possibilities inherent in the affordances of the technology, as well as the interests being served by such a foreclosure.
Identifying the role of contingent factors in shaping the institutionalisation of transactional data does not imply that its future is radically open, as if all that would be needed for it to serve progressive ends is to put the same technology in different hands. However it does foreground the centrality of agency to the establishment of socio-technical systems and the reproduction or transformation they undergo after their emergence: the role played by individuals, networks and organisations, their concerns and vested interests, producing what are later ossified as technical systems inexorably unfolding in a way governed by nothing more than their own technical logic. It makes it easier to ask who are driving these changes, what motivates them and how are their interests served through this labour.
To leave the analysis at this stage would offer an unsatisfying political ontology, presenting a digital capitalism bifurcated between the engineers and the engineered. This offers a dystopian mirror image to the cyber-utopian outlook which presents social change as emerging from the creative actions of a pioneering elite (Turner 2005). Each accords a primacy to technological mediation, seeing it as the engine of either social control or positive transformation, which inclines analysis to an over-estimation of the causal powers of technology and an under-estimation of the causal powers of social structure. This leaves us with an inadequate account of capitalist dynamics, failing to recognise the engineers as operating within firms embedded within a politico-economic context that profoundly shapes their operation (Srnicek 2016). It demarcates technology firms from capitalism as such, seeing the technology sector as sui generis in a way which acts discursively to make an epochal cut (“we are not like other firms”) that obscures genuine novelties at the level of economic firm by implicitly casting it all as novel. It also leaves us with an inadequate account of everyday life under digital capitalism, not merely at the level of phenomenology (i.e. the richness with which digital devices and digital activities, generative of transactional data, come to be experienced by ‘users’) but also the concern which individual users come to have in these data-generating affairs and how this mattering shapes their social action in ways which have important aggregative and collective consequences.
These framings obscure the collective dimension to agency, an oversight which Archer’s (1995) social realism can help us correct. The engineers are themselves primary agents, possessing vested interests through shared social position(s) and the distribution of resources contingently attached to them. Their imagined primacy within digital capitalism is not borne out by the available data, with product managers and designers consistently earning more, even if monthly salaries for engineering interns nonetheless receive twice the media wage for the rest of the United States. While data scientists, infamously described in the Harvard Business Review as the ‘Sexiest Job of the 21st Century’, routinely enjoy higher starting salaries, their growing oversupply seems likely to suppress salary growth (Coren 2016). Academic ethnography, technology journalism and popular culture converge in depicting life in Silicon Valley as presided over by a series of towering figures, enjoying celebrity status in virtue of their business accomplishments, while many thousands of aspirants imagine one day joining their gilded ranks (Marwick 2014, Martinez 2016). Furthermore, the privilege apparently enjoyed by many of these aspirants when considered in national or international terms is complicated when the rapidly spiralling costs of life in the Bay Area and rapidly declining quality of life are factored in.
The political economy of Silicon Valley is complex and simplistic invocations of the engineers as a new political class fail to represent it adequately, even if there are nonetheless important questions we can ask about the emergence of a (variegated) digital elite. This raises issues concerning the collective agency emerging within Silicon Valley, ranging from the sustained growth in the depth and complexity of corporate lobbying activities through to the unusual distribution of political beliefs across these populations (defying familiar distinctions of left and right) and how these are coming to exercise an influence over national and international politics (Ferenstein 2015). Epistemology, ontology and political economy are linked here because it is precisely these people whose agency is occluded in conventional accounts of transactional data which deny their role in its generation, circulation and interpretation (Couldry and Hepp 2017: 4978). ‘Raw data’ is and always will be an oxymoron, with the concerns expressed through its denial being susceptible to empirical analysis (Gitelman 2013). While the vested interests underlying this might be more complex than the self-enrichment of a postulated ‘engineer class’, it would nonetheless be difficult to analyse the converging project represented by this evisceration of the human if interests are expunged from the analysis at the outset. These interests can be served by the projects of engineers and architects even if these interests might not be their immediate concern, if indeed they even recognise them as vested interests they share with similarly situated others.
Much as it is simplistic to invoke a nascent ‘engineering’ class as the direct beneficiaries of digital capitalism, it would be a mistake to construe the ‘engineered’ solely as an atomised and distracted mass. This is one strata upon which transactional data is operating as a social mechanism: facilitating analysis and intervention at the level of the individual in a manner which is intrinsically prone to opacity. The assembly of people under false pretences in a way intended to create misleading impressions of this mobilisation occurred prior to digitalisation. However digital media provide a powerful array of tools which can be used to this end, as well as insulating the instigators from identification or scrutiny (Tufekci 2014). Nagle (2017: 118) argues that those organising against the current American president are now at risk from an “ability to send thousands of the most obsessed, unhinged and angry people on the Internet after someone if they dare to speak against the president or his prominent alt-light and alt-right fan”. This might overstate the case somewhat, reading back ‘an ability to send’, which produces collectivity from the observable fact of converging action, however it accurately recognises the central role played by digital media, particularly Brietbart, during Trump’s ultimately successful campaign for the presidency (Green 2017).
The radical possibilities for mobilising distracted people in this way raises questions about the long-term future of democratic political forms (Carrigan 2016). However there remains the possibility that the reconfiguration of primary agency currently underway might generate collective agents who are not being influenced in such a way. Interventions which bring about a change in the life chances of an aggregate, even one that might not have existed as such in a prior state, concurrently raise issues which those within that group face individually and/or collectively. The inherent opacity of transactional data makes it difficult but by no means impossible for groups to organise collectively around the shared fact of predictive privacy harms or digital enfranchisement. The difficulties which union organisers are now confronting when seeking to organise workers within the gig economy, with labour relations rendered opaque and tenuous, pale into comparison compared with the practical questions of political mobilisation entailed by these subtle forms of harm, disenfranchisement and marginalisation (Woodcock 2015).
However these empirical difficulties do not negate the possibility that these nascent primary agents can be organised into corporate agents, as well as their capacity to organise themselves in this way. The identification of these aggregates has important consequences for how we conceptualise the agency of collectives, as well as that of individuals. Identifying, representing and acting upon populations through ‘big data’ carries consequences for the public who are ‘carved up’ in new ways (Williamson 2017: 62–63). This ‘carving up’ is not new, nor are its effects. While there may have been a gap between the rhetoric and reality of the mid-century advertising business, its ambitions “to call group identities into existence where before there had been nothing but inchoate feelings and common responses to pollsters’ questions” should be taken seriously (Frank 1998: loc 640–657). The market segmentation which became the focus of advertising in the latter half of the twentieth century was partly identification of latent differences within the population and partly an artefact of the methods used to identify those purported differences. What has changed are the means available to this end, offering an unprecedented degree of granularity in the analysis of consumer behaviour and opacity in interventions made on this basis. This might be a matter of primary agency, in Archer’s (1995) sense, with an act categorisation leading to a shift in the life chances facing members of an grouping. The opacity of such data-driven interventions means the patterning of this effect is liable to be unclear, something which can at best be inferred from individual cases in which what Crawford and Schultz (2014) call predictive privacy harms have been established through legal challenge, journalistic expose or activist campaigns. What we don’t know is the potential scale of these harms, as well as how their distribution intersects with existing socio-demographic categories. Such opacity is a characteristic feature of platforms, resulting from the personalisation of user experience and the recourse to ‘corporate confidentiality’ in the face of demands to audit propriety algorithms. It obstructs any move from primary agency to corporate agency, as those harmed by data-driven interventions will often be unable to identify others who are similarly harmed with whom to organise collectively, if indeed they are even cognisant of the harms they themselves have been subject to.
What Tufekci (2014) calls the computational politics emerging from these developments upsets many of our traditional assumptions concerning the public sphere and how grievances are aired within it. The manner in which life chances are liable to be configured by opaque processes poses profound legal and political challenges which academics, activists and policymakers are only beginning to scratch the surface of through initiatives driven by notions such as algorithmic accountability (Pasquale 2015a). These unseen and unheard harms, unlikely to be conceptualised as such by those leveraging the ontological asymmetry of transactional data for their own competitive advantage, find reflection in more easily identifiable forms of inequality which are no less pernicious for being familiar in their operation. As Couldry (2012: loc 1534) points out, the ubiquity of the Internet across sectors increases the salience of digital skills and digital strategies, individual capacities likely to be correlated with socio-economic status and education. While the existing data on the digital divide makes for sobering reading, reminding us that … the tendency within this debate to conceptualise access in zero-sum terms obscures more subtle forms of digital disenfranchisement that seem likely to persist, even as access to the Internet trends ever upwards. The increasing assumption of digital-by-default in the provision of public services risks further excluding those who have fallen behind, as well as symbolically erasing them if transactional data becomes the basis for service-planning as well as service-delivery (Dunleavy 2014).
Andrejavic (2013) goes further and suggests we are liable to see a big data divide emerging, in which the data-rich and the data-poor are forced to orientate themselves towards the social world in diametrically opposed ways. These asymmetries are embedded into the expanding infrastructure of digital capitalism: an infrastructural divide “shaped by ownership and control of the material resources for data storage and mining” and an epistemological one manifested in “a difference in the forms of practical knowledge available to those with access to the database, in the way in which they think about and use information” (Andrejavic 2013: loc 464). The political economy of such a divide eludes the analytical resources of the conventional social sciences, requiring a reconfiguration of disciplinary boundaries to facilitate analysis all the way down to algorithms and all the way up to social structures (Davies 2017). However the digital social science being generated by digital capitalism is not the digital social science we need, if we are to resist the inequities endemic within it.
In this chapter I have argued that the asymmetries we can see produced in so many domains are a necessary rather than contingent feature of transactional data, necessitating that claims made at the level of epistemology should also be analysed at the level of political economy. It is possible to recognise a common intellectual project, emerging in a manner which is tied up with the reconfiguration of vested interests as we move into what Sernicek (2016) calls platform capitalism, without reducing that project to these vested interests. This is what I have described in this analysis as the evisceration of the human: the commitment to the reduction of human agency to the behavioural traces of human action. It is common in the sense of converging rather than coordinated, to be analysed in terms of shared pre-conditions and shared outcomes rather than prior organisation.
It can be found across a range of social domains, in each case animated by different proximate concerns, despite the overlaps which license talk of a singular (albeit diffuse) project. The closest manifestations of it for those working within the academy are data science and computational social science, reflecting a radical empiricism committed to the aforementioned dissolution of human agency. My argument has been that we need to see their emergence as proximate manifestations of a broader trend, itself susceptible to (and urgently necessitating) sociological analysis. To treat the emergence of ‘big data’ within the academy in terms of its epistemological radicalism or methodological novelty obscures a broader transformation taking place, in which positivistic dreams of reading the ‘book of nature’ expand to incorporate a similarly mathematicised ‘book of society’ (Barnes and Wilson 2014). The epistemic hubris which has come to surround what Little (2015) calls “the utopia of social legibility”, as well as the projects which respond to it while also seeking to bring it into being, can be framed in terms of the longue durée: a new form of social science emerging concurrently with a new phase of capitalism (Bratton 2016; Srnicek 2016). It is one which takes the ‘online order’, profoundly shaped by corporate actors, as the given foundation for a social science conducted within the boundaries of these established platforms and constrained by their ever-shifting conditions. Analysis of these issues is plagued by the problem of self-reference: it is itself part of the reconfiguration of knowledge production which it is purporting to analyse. In this chapter I have attempted to lay some of the conceptual groundwork for addressing these issue in a systematic way, though it is undoubtedly a project which exceeds the scope of what is possible in a single text. It is nonetheless crucial if we hope to resist the emergence of a digital social science which is unable to ask systematic questions about the digital capitalism which has produced it. Unless this trend is abated, the possibility of resisting the evisceration of the human will decline precipitously.
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