Foreseeing Race: The Technology and Culture of Risk Prediction after the Datalogical Turn

deadline for submissions: 
June 15, 2020
full name / name of organization: 
Journal of American Studies (Cambridge University Press)

Foreseeing Race: The Technology and Culture of Risk Prediction after the Datalogical Turn 

Special issue, Journal of American Studies


Georgiana Banita (University of Bamberg)

R. Joshua Scannell (The New School)

The current crisis of legitimacy in Big Tech and AI provides an opening for forceful scholarly criticism of predictive and surveillant technologies’ impacts on social life. The erosion of the supposed trustworthiness and beneficence of the industry as a whole, and the Big Four (Apple, Google, Facebook, Amazon) in particular, has precipitated a discursive disillusionment with tech. And, while this has raised questions of technological racism in certain segments, the broader role that race plays in driving the bad actions of the tech industry remains underreported and undertheorized. Perhaps more importantly, there is a real opportunity here to imagine forms of struggle and liberation that may arise through tech, but certainly will not do so by themselves. In other words, by focusing on racialized technology in an American context, we hope to intervene in assumptions that the answer to these forms of racism is merely “better” technology, or instead depends on a rethinking of the terms of the discussion.

To name one controversial example: Big Data surveillance and risk prediction have recently gained prominence within public safety and law enforcement circles. Algorithmic decision-aids, which encode criminological theories about crime rates and process vast amounts of data into patterns and trends, have applications that range across several fields from sentencing and the anticipation of recidivism to predictive policing. Even though it remains unclear to what extent predictive crime analytics systems absorb human biases, the technology is already widespread in the US, UK, and continental Europe. Recent work in sociology, political science, and computational social sciences as well as high-profile human rights investigations have launched a much-needed critical narrative by demonstrating that predictive algorithms undermine equal justice and preclude individualized assessments. While literary and cultural studies have been slower to recognize the amplifying effect of unfair algorithms on existing disparities of race, their methods of diachronic analysis and increasing societal engagement have much to offer in answering key questions. How did predictive technology gain social acceptance? And which historical strategies of racial oppression inform contemporary methods of data mining and crime forecasting?

In her celebrated examination of data-based inequality, Virginia Eubanks argues that the world is enveloped in an inscrutable network of “informational sentinels” that frame and allocate the distribution of resources and privation outside of human agency or oversight. More specifically with regard to race, new forms of racial profiling that Safiya Noble has termed “technological redlining” consolidate existing racial biases, inequalities, and the maldistribution of life chances while formally appearing to operate “race blind.” In focusing on digital red flags attached to people of color, these and other sociological studies have uncovered the significant role of data discrimination in the perpetuation of racism during the 21st century. Recent scholarship by Ruha Benjamin about what she designates “the New Jim Code” has additionally proven the benefits of tracking present algorithmic tools to past techniques of promoting racial discrimination and White supremacy. 

This assemblage of techniques and technologies is designed to measure and manage human capacities, predict tendencies, and control bodies in space and time without ever conjuring a “human” referent as such. Instead, an array of systems generates and sifts data black boxed from human comprehension and abstracted from any recognizable set of human properties, yet output consequences of vulnerability and premature death to the same groups of people that are historically and systemically marginalized. Patricia Clough et al have called this mode of governmentality the “datalogical,” a sort of technical read/write program for racism-by-proxy that writes racial formations even as it reads disembodied and decontextualized “data.”  

Given the long durée and infrastructural nature of racial bias in the US, literary and cultural methods are well-positioned to engage with the continuities of racial imaginaries and thereby reveal the occluded premises of racialized prediction in the present. Furthermore, querying the purported advantages of state and infrastate surveillance and prediction systems can revitalize cultural, ethical, and aesthetic debates on the uses of narrative and visual media in making sense of this disquieting morphological relation between individuals and institutions of social control. Can the toolkit of cultural studies reveal a clearer genealogy of digitally-driven surveillance and crime analytics? And might perhaps the collating, speculative nature of cultural interpretation itself not be entirely dissimilar from the practices of automated intelligence? 

In navigating this terrain, our interdisciplinary special issue aligns contemporary American and British scholarship in the area of race and digital technologies with broader cultural theorizations of how race works as a structuring agent in the history and imaginary of the United States. The essays will share a commitment to political and social critique while adopting cultural studies approaches to explore the racialized dimension of Big Data surveillance; the racial inequities embedded in prediction technologies; and the problematic invisibility of algorithmic (in)justice. The special issue will thus provide a US-focused cultural conceptualization of predictive technology within the emergent fields of automation studies and the ethics of Big Data. 

Potential topics include but are not limited to: 

Law Enforcement 

-   the use of socio-politically derived Artificial Intelligence in law enforcement

-   epistemologies and temporalities of predictive policing

-   alternative frameworks for rethinking the future of race and high-tech policing

-   aesthetic and narrative approaches to crime forecasting

-   continuities between digitally-driven racialized surveillance and “analog” methods (e.g., Terry Stops, broken windows policing, etc.)


-   militarized surveillance practices in formally non-conflict environments (especially drone surveillance)

-   countermeasures to racialized Big Data surveillance (including cloaking and the development of alternative “black data”)

-   statehood, governmentality, and the surveillance of race

-   relationship of digital surveillance and prediction to broader extractive practices of racial capitalism

Cultural Practice 

-   literary, visual, and quotidian responses to surveillance and technologies of prediction 

-   historical precedents and roots of current algo-racism 

-   history and cultural production around the concept of prediction

-   racialized prediction in the context of Afrofuturism, technology, and the posthuman 

We are asking for abstracts of around 500 words by June 15. Article drafts of 8,000 to 12,000 words will be due by December 15. Please email abstracts and queries to both editors at: and