Emerging Forms of Citizenship
The technological mediation of state-citizen relations engenders particular kinds of risk associated with digital governance and biopolitics that significantly differ from Foucault’s notion of governmentality. In State Power and Technological Citizenship in India: From the Postcolonial to the Digital Age, Itty Abraham and Ashish Rajadhyaksha lay out a genealogy of Indian biopolitics from the colonial period to the present. They draw out the tension between geopolitics and biopolitics in relation to the state’s need to identify who is a citizen/resident for the provision of social services, emphasizing that citizenship here is understood as an emergent political outcome. They conceptualize “technological citizenship” as a way to understand how technologies mediate state-citizen relations.
Reflecting on the ways in which citizenship as a form of political subjectivity is shaped by digital politics, Engin Isin and Evelyn Ruppert, in the second edition of Being Digital Citizens, argue that digital citizenship is a form of making claims to rights through the internet. Attempting to move beyond accounts of life with/in the internet that rely on the dystopian-utopian binary, they note that being in cyberspace is best understood as a continuous space of action, rather than as a question of whether a citizen is online or offline. They also outline the collectivity embedded in this notion of citizenship as a form of political subjectivity by noting that the work of enacting rights is collective, global, and transversal, emerging across borders.
Large-scale data systems are integral to the work of bureaucratic management of citizens. As Ranjit Singh and Steven J. Jackson note in Seeing Like An Infrastructure: Low-resolution Citizens and the Aadhaar Identification Project, the implementation of these data systems is uneven in far-reaching, exclusionary, and distributed ways. While attending to the ways in which these data systems operate as infrastructures, Singh and Jackson also highlight that ongoing work of street-level bureaucrats in representing citizens and of citizens in claiming representation through data mutually shape state-citizen relations in India. Taking India’s biometrics-based identification project, Aadhaar, as an example, they argue that the challenges involved in the implementation of three key processes in Aadhaar have resulted in experiences of citizenship that can be mapped on a spectrum of entity resolution. At one end of this spectrum lie high-resolution citizens, whose rights and entitlements have been expanded through Aadhaar’s processes, and at the other are low-resolution citizens, whose rights and entitlements are curtailed.
Emerging Forms of Statehood
Before looking at the emerging role of algorithms in statecraft, we took a detour into the following question: What is an algorithm, and how should it be studied and understood? In Algorithms As Culture: Some Tactics for the Ethnography of Algorithmic Systems, Nick Seaver makes the case for researching algorithms as “multiples” that are enacted in the ways in which a broad array of stakeholders engage with them, including the researcher. These enactments are situated in and produce knowledge from the inevitably partial perspective of the stakeholder who does the work of enacting, often at the expense of excluding other positionalities. Offering some methodological tools to study (and participate in) the enactment of algorithms, Seaver notes that it is generative to approach algorithms “as” culture, and as sites for empirical engagement, rather than “in” culture/as discrete, static objects.
Outlining the contours of statecraft in the digital age in Learning Like A State, Marion Fourcade and Jeffrey Gordon point to ways in which the deep entanglements of the state and the market engender a new form of governmentality, i.e., the dataist state. The concept, in turn, is borrowed from the work of Yuval Harari, who defines it as an “ascendant belief system” that “declares that the universe consists of data flows, and the value of any phenomenon or entity is determined by its contribution to data processing” (Page 428). The dataist state conceives of its citizens, its infrastructure, and itself as streams of data, and this orientation toward numerous streams of data in turn shapes state-citizen interactions such that social problems are seen primarily through individual and behaviorist lenses. As they note, too, this mode of statecraft further blurs boundaries between the state and the market. They argue, however, that there is a strong need for the state to “see like a citizen,” i.e., to engage in statecraft through the perspective of those who are affected by the many problems that dataism gives rise to, rather than through a focus on surveillance, evaluation, and prediction.
In Processing Alterity, Enacting Europe: Migrant Registration and Identification as Co-Construction of Individuals and Polities, Annalisa Pelizza shows how the process of contending with populations that were previously unknown to European actors and providing them “European-legible” identities reflects and illustrates the challenges of infrastructuring Europe. The work of population management makes room for an enactment of the ‘us’ vs. ‘them’ boundaries in ways that are inextricably intertwined, at once enacting the individual Other as well as the legal-bureaucratic forms of order that constitute Europe as a geographic space.
Finally, in a recent review, The Society of Algorithms, Jenna Burrell and Marion Fourcade lay out the social implications of algorithmic transformation across a number of domains. They note, in particular, that the widespread adoption of techniques of mathematical optimization has caused decision-making at the state and organizational levels to be governed by actuarial logics, which in turn has reshaped existing pathways of social reproduction and mobility. Discussing the ways in which AI shapes and is shaped by society is much more a question of who will come to benefit and in what ways, rather than a question of whether there will be any benefit at all. They end their expansive review by acknowledging the simultaneous everydayness of AI as a human form of control innovation, while also acknowledging the ways in which it creates a new coding elite.
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