Nick Couldry (2020) raises the point that critical data studies is not as critical as it needs to be. Looking back on the theoretical approaches that have come to the fore of critical data scholarship over the past five years or so, Couldry is therefore concerned with how “the possibility of social critique” might be recovered in this space. As he initially puts it:
“If a major intellectual, indeed civic, battle about datafication and its implications for ‘society’ is under way, how well-placed are the social sciences to wage this battle? … Do we have the tools to get in view what is problematic about datafication for social life? Do we have a clear enough idea any more of what should count as critique, and on what empirical and normative resources it depends?” (Couldry 2020, p.1136)
Couldry’s concerns stem from the apparent dominance in recent critical studies of data of approaches rooted in STS (science and technology studies)– most notably work that draws upon Actor Network Theory (ANT) and its various iterations and incarnations.
On one hand, Couldry acknowledges that STS studies offer a welcome “attention to complexity” and build rich descriptions of the complex interconnections and relationships that underpin the people, actions and resources that constitute contemporary data infrastructures. In particular, STS approaches offer a powerful means of teasing out how these networks come together, and what roles they play in shaping data processes and institutions, as well as the formation of data publics
Yet, Couldry also makes the point that STS is based around a distinct ‘flat ontology’ that lends itself to mapping and describing networks, while doing little to address more critical questions about the nature of social order. In particular Couldry highlights the tendency of STS studies to pay little attention to the distinctive position of human agents within data assemblages, as well as often failing to pay close attention to the larger social order in which a particular assemblage emerges and stabilizes.
Couldry therefore makes a case for paying “less deference” to STS, and more closely aligning critical data studies with critical sociology approaches that focus squarely on the role of data in reconfiguring the overall order of social life. This raises questions about the politics of datafication and the new forms of power that are exerted through data assemblages – not least the embodied agency of the reflexive human subject, as well as consequences of datafication for the constitution of social knowledge and the social world. As Couldry contends, this focuses our attention on the crucial question that underpins the critical data studies approach – i.e.:
“… how is the overall order of social life being reconfigured to promote particular corporate and governmental interests on the basis of new and radical forms of reduction – the reduction of human life to configurations from which profit through data can be maximally extracted?” (Couldry 2020, p.1140)
Couldry expands on this question in the form of three interlinked areas of inquiry that critical data studies needs to address through the extended use of critical social theory:
- The established ways in which what counts as social knowledge, and who/what counts as an input to social knowledge, is changing. Here Couldry gives the example of our traditional understandings of poverty as a socially caused phenomenon that needs to be address by giving the poor more favourable terms. In an era of big data, this knowledge is likely to be reconstituted along data-driven lines – for example, the category of being ‘poor’ calculated in terms of their previous credit-related behaviour’, and the future treatment of those who are designated ‘poor’ being calculated in terms of avoidance of further commercial risk.
- The ways in which this is changing our conception of ‘society’ as a whole. While this automated and algorithmic knowledge might not replace existing social knowledge altogether, these new datafied models of social knowledge are likely to not acknowledge (let alone draw upon) older forms of expertise and judgement. In this sense, our overall conception of ‘society’ might well begin to follow these data-driven forms of social knowledge.
- The ways in which resulting new forms of ‘social knowledge’ now constitute practical understanding of what is socially actionable. In turn, then, we need to pay attention to how humans begin to accept – and expect – that new forms of social knowledge should be grounded in how data-driven systems and machines interpret the world, rather than humans. For example, this might be seen in the belief that machines are able to ‘know’ more about humans than the humans know about themselves.
Couldry offers some suggestion of how established forms of critical sociology and critical theory can be brought to be bear on these questions of social order, social values and social epistemology. For example, he suggests that accounts of how relative social order emerges from data infrastructures might draw on Norbert Elias’s notion of ‘figuration’ – thus highlighting the position of human beings within data-driven networks, and the moral tensions that arise from the resulting patterns of interdependence. Similarly, questions of how social order is sustained might explore issues of definitional power through theorists such as Luc Boltanski. They might also draw on ideas of representational and categorical power from the likes of Judith Butler – not least Butler’s work on how powerful institutions regularly recognize some people as significant, and other as not. Finally, Couldry reminds us that critical sociology has an inherent affinity toward questioning the forms of capitalism that underpin datafication. Here Couldry points to Marxian theorists such as Moishe Postone, whose work can foreground the larger social and economic forces shaping new data-driven social orders, and crucially raise the moral question of what consequences these social orders might have for human beings and the things they value.
All told, Couldry argues that these additional perspectives and theory-driven re-focusings might push critical data studies toward interrogating the ways in which data is becoming an organizing principle across all aspects of society, the ways in which corporate and government actors are contriving to build different types of social order through datafication, and the forms and dynamics of the data-driven processes that lie behind these reorganisations. In this sense, critical sociology can expand the horizons of critical data studies toward “processes of social formation themselves on the largest scale”.
Couldry, N. (2020). Recovering critique in an age of datafication. New Media & Society, 22(7), 1135-1151.