Situating questions of data,power,and racial formation

Abstract

This special theme of Big Data & Society explores connections, relationships, and tensions that coalesce around data, power, and racial formation. This collection of articles and commentaries builds upon scholarly observations of data substantiating and transforming racial hierarchies. Contributors consider how racial projects intersect with interlocking systems of oppression across concerns of class, coloniality, dis/ability, gendered difference, and sexuality across contexts and jurisdictions. In doing so, this special issue illuminates how data can both reinforce and challenge colorblind ideologies as well as how data might be mobilized in support of anti-racist movements.

This article is a part of special theme on Data, Power and Racial Formations. To see a full list of all articles in this special theme, please click here: https://journals.sagepub.com/page/bds/collections/dataandracialformations

Introduction

Although datafication promises better-organized information that captures contextualized phenomena and expedites decision-making, big data is shaped by legacies of inequality that can enable material and representational harms. Critical observers have warned that artificial intelligence (AI), big data, and other so-called ‘smart’ technologies threaten not only to automate discrimination and oppression but to become central mechanisms through which racism operates (Benjamin, 2019; Noble, 2018; Barocas and Selbst, 2016; Stark, 2018). Extending these insights, scholars of critical data studies have scrutinized how big data contributes to processes of racialization. They provide important analyses of the pervasiveness of whiteness in AI and machine learning (Birhane and Guest, 2020; Cave and Dihal, 2020; Phan, 2019; Schlesinger et al., 2018), the limitations of anti-discrimination and “fairness” approaches to race and other social hierarchies in machine learning (Hoffmann, 2019), strategies for operationalizing the multidimensionality of race in sociotechnical systems (Hanna et al., 2020), and frameworks for addressing racialized harms, such as algorithmic reparation (Davis et al., 2021).

This scholarship evinces how big data co-produces racialized social phenomena and inequalities, extending claims that data and datafication are cultural processes (e.g. Friedman and Nissenbaum, 1996; Gitelman, 2013; Kitchin, 2014). Racial co-production is not limited to critical data studies; it intersects with critical conversations that span critical race theory (CRT), postcolonial studies, the sociology of race and ethnicity, science and technology studies (STS), among others. Work in these allied fields provides important insights into how race and racism are deeply entangled in the collection, use, and deployment of data, which have been gleaned through analyses of classification (Goldberg, 2001; Zuberi, 2001), methodology and disciplinary practice (Daniels, 2013, 2015; Walter and Andersen, 2013; Zuberi and Bonilla-Silva, 2008), racialized social control and surveillance (Browne, 2015; Monahan 2010), and liberation (Coleman, 2009; Kadiri, 2021). They demonstrate how there is much to be gained within data studies—theoretically and practically—from deepening engagement with intellectual schools of thought that have long been concerned with race and racism.

This thematic special theme explores how data and technological platforms constitutively contribute to contemporary racial hierarchies, attending to both sociocultural and material implications. The papers in this collection showcase interdisciplinary insights from scholars working across fields of gender studies, library and information sciences, Internet and media studies, STS, socio-legal studies, and sociology. Drawing together case studies and theoretical explorations, authors make productive inroads in new and emergent conversations regarding how data emerge in and through racial projects as they intersect with systems of class, colonialism, dis/ability, gender, and sexuality. They illustrate how explicit engagement with interdisciplinary theories of race and racism can enhance understandings of big data's material impacts and can inform means of addressing these impacts. In doing so, the articles and commentaries not only contribute to ongoing scholarly debates about how data are mobilized to innovate, interrupt, and even generate racisms, but also aid in identifying strategies to support anti-racist and sovereignty movements.

Unpacking data, power, and racial formations

Considering big data as a mechanism of racialized power prompts a range of critical questions. How do modes of datafication normalize racial classification systems and mask their sociocultural underpinnings? To what extent can big data work in the service of liberatory agendas? What are the opportunities and risks of practices, protections, and systems that promise more equitable outcomes? These questions are especially important when faced with the “seduction” of data-driven knowledge production and quantification (see Merry, 2016).

Recognizing that others are asking these questions in relation to data sets and data set development (Scheuerman et al., 2021; Buolamwini and Gebru, 2018), model development and racial classification (e.g. Hanna et al., 2020; Angwin and Larson, 2016), and the production of race on digital media platforms (e.g. Brock, 2009, 2020; Tynes et al., 2011), this special theme considers the dyanamic relationships between datafication and racial formation. In reference to the racial formation, a term commonly associated with work by sociologists Omi and Winant (1994: 12), we mean how race becomes “defined and contested throughout society, both in collective action and personal practice”, with a focus on the processes “by which social, economic, and political forces determine the content and importance of racial categories, and by which they are in turn shaped by racial meanings”. Racial formations mark historical, political, and social processes through which power takes shape and becomes articulated in and through racial categories. Earlier analyses that share these concerns attend to how data have operated in the service of substantiating and transforming social categories of difference across contexts and jurisdictions (e.g. Chun, 2009; Goldberg, 1997; Hammonds, 1997; Reardon, 2004). More recent scholarship focuses on the sociocultural implications that affect racial hierarchies, challenges colorblind understandings of data and algorithms, interrogates how technological platforms discipline social interaction, and examines how data become animated through situated knowledge (Browne, 2015; M’charek et al., 2013; Muhammad, 2011; Noble and Tynes, 2016; Walter, 2016).

This collection captures connections and tensions between data and racial formation across different scales, sites, and structures, reflecting on how they manifest in lived experience and representational forms. Here, authors use and extend analyses of racial formation by illustrating how data can operate in the service of substantiating and transforming inequalities across contexts and jurisdictions. In sum, the papers in this special theme address how data become implicated within the interlocking systems of domination and oppression that affect everyday lives and livelihoods.

Overview of this special theme

The collection features analyses that illustrate how data are mobilized to innovate and interrupt forms of racism. Their findings illuminate how data can both instantiate and challenge colorblind ideologies. Providing nuanced insights about interlocking inequalities, this special theme advances theoretical understandings of data and racial formation and offers points of caution for anti-racist movements. As calls for data-driven systems for social good and demands for technology in the public interest have gained traction in recent years, these contributions are particularly timely: they provide many examples that demonstrate the importance of attending to sociopolitical, subjugated, and technical knowledges when disentangling the materialities of data production, advocacy, and critical data-related inquiry.

The opening commentary by Phan and Wark (2021) takes up Gilroy's provocative claim that “the time of ‘race’ may be coming to a close” (1998: 840) as a starting point for reconsidering how the mediated nature of datafied processes evince shifts in racialization. They ask: As regimes of computation are largely opaque modes of classification, what does race become? The commentary documents epistemological shifts in which racialized subjects emerge through assemblages of data, revealing a new regime that they refer to as “racial formations as data formations”.

Hatch (2022), author of the first article in the theme, examines how the governance of coronavirus disease 2019 (COVID-19) data became central to addressing racism in the health and health care in the United States, acknowledging a common view that racialized COVID-19 health disparities would have been greater without this data. Hatch challenges this idea by querying whether the production and circulation of racial health data strengthened anti-Black racism. He traces how metrics of racial death are mobilized to institute racist social laws, policies, and systems. Using the metaphor of “racial antimatter” to capture how statistics can represent the social world in ways that fail to correspond to lived experiences, Hatch (2022: 6) examines how data work in the service of weaponizing knowledge of racial inequalities.

The third contribution to the theme, an article by Henne, Shelby, and Harb (2021), illustrates how racial capitalism can enhance understanding of data capital and inequality through an in-depth study of digital platforms used for intervening in gender-based violence. Examining how reporting apps use data to support institutionally legible narratives of violence, the authors draw attention to how reporting reinforce racialized property relations built on extraction and ownership, the capital accumulation that reinforces the inequitable distribution of benefits derived through and from data, and the commodification of diversity and inclusion.

Sooriyakumaran’s (2022) commentary is similarly concerned with racialized inequalities etched and shaped by capitalist relations. Their scope and focus, however, begins with localized encounters through an autoethnographically informed reflection to trace the impacts and implications of digitized residential tenancy databases in Australia. Demonstrating how residential tenancy databases are racialized technologies with colonial underpinnings, Sooriyakumaran's analysis (2022) articulates the need for multifaceted frameworks that attend to how racial capitalism, state surveillance, and colonialism continue to operate—in this case, in and through tenancy databases.

The next article by Crooks (2021) examines non-profit efforts to make public schools data driven through the aggregation, analysis, and visualization of digital data. Drawing on theoretical explanations of racialized organizations (Ray, 2019), the analysis illuminates a form of productive myopia, ‘a way of pursuing racial projects via seemingly independent, objective quantifications’ (Crooks, 2021: 2), which enables claims that data can reduce the impacts of racial inequalities while also facilitating them. This grounded approach highlights how racial projects are taken up in public education through EdTech and data-driven dashboards.

The concluding commentary by Anantharajah (2021) examines how racial formation takes shape through data projects, drawing on ethnographic research on climate finance governance conducted in Fiji. Her explanation of how climate finance organizations develop and use data projects to support flows of capital targeting the Pacific elaborates on how such practices are mediated through schemas with both colonial and racial contours—lenses that have racializing implications even though they are not visible on the surface.

Taken together, the articles and commentaries presented in this special thematic theme engage longstanding and emergent concerns regarding data's role within the racial formation, attending to recent cultural and political developments as well as geopolitical and sociotechnical shifts. They showcase how data are not only enrolled in processes of racial formation, but also how they intersect with projects of class, dis/ability, gender, and sexuality as well as other social categories of difference. We hope the collection serves as a productive resource for readers from a range of fields and contributes to a generative dialog that crosses disciplinary boundaries.