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Situating Questions of Data, Power, and Racial Formation

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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.
Situating questions of data, power,
and racial formation
Renee Shelby and Kathryn Henne
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 sub-
stantiating and transforming racial hierarchies. Contributors consider how racial projects intersect with interlocking sys-
tems 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.
Keywords
Data, racial formation, power, intersectionality, algorithmic bias, datacation
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 datacation promises better-organized informa-
tion that captures contextualized phenomena and expedites
decision-making, big data is shaped by legacies of inequal-
ity that can enable material and representational harms.
Critical observers have warned that articial intelligence
(AI), big data, and other so-called smarttechnologies
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 contri-
butes 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 limita-
tions of anti-discrimination and fairnessapproaches to
race and other social hierarchies in machine learning
(Hoffmann, 2019), strategies for operationalizing the multi-
dimensionality 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 datacation are cultural processes
(e.g. Friedman and Nissenbaum, 1996; Gitelman, 2013;
Kitchin, 2014). Racial co-production is not limited to crit-
ical 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 elds
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
School of Regulation and Global Governance (RegNet), The Australian
National University, Canberra, Australian Capital Territory, Australia
Corresponding author:
Renee Shelby, School of Regulation and Global Governance (RegNet), The
Australian National University, HC Coombs Extension Buliding #8, 8
Fellows Road, Canberra, Australian Capital Territory, Australia.
Email: reneeshelby@google.com
Creative Commons NonCommercial-NoDerivs CC BY-NC-ND: This article is distributed under the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial
use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original workis
attributed as specied on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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DOI: 10.1177/20539517221090938
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classication (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 studiestheoretically and practicallyfrom deepen-
ing 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 con-
temporary racial hierarchies, attending to both sociocultural
and material implications. The papers in this collection
showcase interdisciplinary insights from scholars working
across elds 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 datas 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 sover-
eignty 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
datacation normalize racial classication 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, protec-
tions, and systems that promise more equitable outcomes?
These questions are especially important when faced with
the seductionof data-driven knowledge production and
quantication (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 classication (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 datacation 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 dened
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 forma-
tions 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 dif-
ference 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 under-
standings of data and algorithms, interrogates how techno-
logical platforms discipline social interaction, and examines
how data become animated through situated knowledge
(Browne, 2015; Mcharek 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, reecting 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 dom-
ination 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
ndings illuminate how data can both instantiate and chal-
lenge 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 import-
ance of attending to sociopolitical, subjugated, and tech-
nical knowledges when disentangling the materialities of
data production, advocacy, and critical data-related inquiry.
The opening commentary by Phan and Wark (2021)
takes up Gilroys provocative claim that the time of
racemay be coming to a close(1998: 840) as a starting
point for reconsidering how the mediated nature of dataed
processes evince shifts in racialization. They ask: As
regimes of computation are largely opaque modes of classi-
cation, what does race become? The commentary
2Big Data & Society
documents epistemological shifts in which racialized sub-
jects emerge through assemblages of data, revealing a
new regime that they refer to as racial formations as data
formations.
Hatch (2022), author of the rst 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 antimatterto
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 inter-
vening 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 benets derived through
and from data, and the commodication of diversity and
inclusion.
Sooriyakumarans (2022) commentary is similarly con-
cerned with racialized inequalities etched and shaped by
capitalist relations. Their scope and focus, however,
begins with localized encounters through an autoethnogra-
phically informed reection to trace the impacts and impli-
cations of digitized residential tenancy databases in
Australia. Demonstrating how residential tenancy databases
are racialized technologies with colonial underpinnings,
Sooriyakumarans analysis (2022) articulates the need for
multifaceted frameworks that attend to how racial capital-
ism, state surveillance, and colonialism continue to
operatein this case, in and through tenancy databases.
The next article by Crooks (2021) examines non-prot
efforts to make public schools data driven through the
aggregation, analysis, and visualization of digital data.
Drawing on theoretical explanations of racialized organiza-
tions (Ray, 2019), the analysis illuminates a form of pro-
ductive myopia,a way of pursuing racial projects via
seemingly independent, objective quantications(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
nance governance conducted in Fiji. Her explanation of
how climate nance organizations develop and use data
projects to support ows of capital targeting the Pacic ela-
borates on how such practices are mediated through
schemas with both colonial and racial contourslenses
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 datas role within the racial
formation, attending to recent cultural and political devel-
opments 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 elds and contributes to a generative dialog that
crosses disciplinary boundaries.
Declaration of conicting interests
The authors declared no potential conicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The authors received no nancial support for the research, author-
ship, and/or publication of this article.
ORCID iD
Renee Shelby https://orcid.org/0000-0003-4720-3844
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