Resisting Data Capitalism: Browsing „Data for Black Lives”

Something that I feel kept coming up during our course discussions around race and/as technologies and the literature we worked with was the question of a possible subversion of racializing/racialized technologies, not just theoretically, but practically. Are there wholes to slip through, glitches to amplify, fissures to crack open to evade and break systems of automation, surveillance, and control? Is there room for a critical practice that truly allows for an emancipatory use of technology despite of its being shaped and determined by systemic racism in capitalist societies?

There are more and more activist initiatives working towards building a (seemingly paradoxical) resistance. I came across the web space hosted by “Data for Black Lives” (D4BL), a US-based grassroot organization whose founder Yeshimabeit Milner is determined to “us[e] data science to create measurable changes in the lives of Black people”^[1]. The initiative’s objective is to critically engage with digital technologies in order to make them accessible to BPoC and to integrate them into political organizing. At the same time, they acknowledge the historical contexts of capitalism and colonialism which have shaped and continue to shape technologies according to racist bias.

The navigation bar of the website offers plenty of sections to browse through:

•  A blog provides articles by members and associates of D4BL on topics such as the history of and current struggles around technology and resistance in Detroit and racial disparities in Covid-19 vaccination data.

• Under ‚Conference‘, visitors can watch recordings of the annual conference D4BL hosts (there have been three so far).

• The link ‘Action’ provides an overview of the spreadsheets, campaigns, open letters, hashtags, etc. D4BL has gathered, initiated, and supported.

• In the section ‘Programs’, one can gain insights into the organizational structures and the conceptual programs of the different communities involved with D4BL.

• On their Instagram, they share informative as well as entertaining content, i.e. a series of explanatory videos on topics such as predictive policing or facial recognition.

Especially fitting with the context of our seminar, in my opinion, is the newly released report on “Data Capitalism”^[2], which is available for download on a separate website. I would like to summarize the core arguments outlined in the publication and some possible points of critique. The paper offers an introduction to the concept of data capitalism as the analytical framework for the systemic economic and social inequalities in American society, prevalent today. The authors focus on the role of big data and algorithms as central to big companies’ exploitative and oppressive strategies for profitability. The collection and use of data for commercial as well as regulatory purposes is identified as a predominant cause for increasing racial and economic disparities in American society. Another key issue discussed in the report is the history of the commodification of Black people during slavery and its continuity in the use of digital technologies today. A link is drawn between the dehumanization (in the form of datafication) of black people by the chattel slavery and algorithmic technologies which blind to racist bias by operating with ostensibly ‘objective’ data. In a conclusionary effort to promote a proactive perspective on the possibility of resistance, the authors discuss examples of community organizing against big companies such as Amazon or Facebook. The report insists on data capitalism not being inevitable and advocates for actions aiming at policy changes.

This notion of “policy shifts”^[3] as the goal of organized action is debatable, in my opinion. It ignores the structural dimension of systemic inequalities by focusing on merely ‘cosmetic’ improvements. This same critique could be applied to another analytical shortfall of the paper, namely the generalizing condemnation of big tech companies and an ominous political elite. In the summary provided on the website, it is stated that

„Although data capitalism was built by corporations, the government and those who hold power determine how it plays out. Together, their actions determine who data capitalism harms and who it benefits“^[4]

This evokes a strange narrative of ‘good vs. evil’, brushing over the intricate dynamics of power relations and agency in capitalist societies. The authors could have argued in a more convincing way, differentiating between various technologies of data collection and storage and their specific purposes and ways of application (criminal justice system, surveillance technologies, commercial algorithms…). This would have allowed for a structural analysis of data capitalism as a system with multi-leveled implications. Instead, their discussion of powerful institutions (tech companies and the government) reifies the conceptual separation of a ‘public’ and a ‘private’ sphere and thereby disarms the fight for a system change. The theoretical figure of data capitalism does not seem sufficiently articulated in all its complexities and is thus not yet useful for a consequent problematization of the racist, capitalist system it perpetuates.

Still, the report explores modes of action based on a fundamental critique of racializing and racist technologies. Looking at it as part of the collection of information on D4BL, it can certainly offer productive tools for organizing resistance against an unjust and exploitative usage of data-based technologies.

---

^[1] Data for Black Lives (without date). About Us. Online: https://d4bl.org/about.html. Last accessed: 26.06.2021.

^[2]  Yeshimabeit Milner (Data for Black Lives)/ Amy Traub (Demos) (2021). Data Capitalism and Algorithmic Racism. Online: https://datacapitalism.d4bl.org/?utm_campaign=later-linkinbio-data4blacklives&utm_content=later-18297283&utm_medium=social&utm_source=linkin.bio. Last accessed on 26.06.2021.

^[3] Ibid.: 4.

^[4] Text on website, based on report. Section 2. Slavery, the Origin Story.