Session Chair: Ariadna Matamoros-Fernandez
Presentation 1
The Entrepreneurial Gaze: On the Subjectivity of the Tech Elite
Robert Dorschel
University of Cambridge, United Kingdom
Digitalization processes are increasingly associated with intensified domination. Scholars have unearthed how tech companies exert unprecedented power in the economic field through new modes of accumulation, production, and control. Less attention has been paid to the dominant groups operating digital capitalism. It remains largely unexplored what kind of class-specific subjectivities characterize the upper echelons of the tech industry. This article addresses this gap through an analysis of the entrepreneurial gaze of the tech elite. Drawing on a unique data set from Y Combinator, a prominent Silicon Valley-based “accelerator” that mentors early-stage entrepreneurs, the study explores how the ideal tech entrepreneur is discursively constructed. Three central schemas are identified: (1) need-spotting through personal experiences; (2) a faithful vision; and (3) a short-cut orientation. While outlining these socially-organized ways of seeing the world, the article reveals how they not only incentivize exploitative political-economic structures but also enable processes of elite class reproduction.
Presentation 2
Policing Immigrant Indebtedness on Social Media: Navigation of Gratitude, Political Subjectivation, and ‘Surveillance from Home’.
Limichi Okamoto
London School of Economics and Political Science, United Kingdom
This paper discusses the mediated policing of ‘indebtedness’ narratives espoused by immigrant-political influencers towards their host country and people, as a form of valorised _self_-regulation and _self_-assessment with regards to the extent and effectiveness of assimilation — of both themselves and perceived fellow immigrant others. Simultaneously, it explores social media platforms as a space for negotiation between immigrant self-regulation and policing efforts positioned as ‘from home’.
As a case study, I conducted critical discourse analysis of posts and comments on social media platforms (Instagram, X, YouTube) around the 2024 Taiwanese Presidential elections. I focus on the posts made and shared by political influencers, or ‘micro-celebrities’, who are Hong Kong immigrants in Taiwan. Concurrently, attention is placed on linked posts or comments by users self-presented as based in and/or from Hong Kong.
Drawing from the intersections of citizenship, media, and migration studies, I argue how ideas around ‘indebtedness’ function to mould immigrants in accordance to particular valorised and ethnicised national subjects, with abjecting and othering implications. I show how emotive ‘indebtedness’ is incorporated into understandings of civic practices that demarcate worthy members of the host society. The policing of ‘indebtedness’ from both proximate and distant political influencers is positioned as an attempt to delimit the abjected immigrant — the spoilt and incompatible ‘bad egg’ that ruins the life chances of everyone else.
Presentation 3
Predictions of the Self: AI and The Political Economy of Subjectivation
Luciano Frizzera
Concordia University, Canada
The recent widespread availability of Artificial Intelligence (AI) technology and the extensive records of human activities and behaviour in digital format present serious challenges related to how individuals construct their own identities and social relations. AI systems datafy our body and our sense of self, producing a new cartography of biopower (Foucault, 1982) and a new form of the political economy of subjectivation (Langlois & Elmer, 2019) that treats individuals as objects from which raw material is extracted to produce predictive models that act as our data doubles (Haggerty & Ericson, 2000). Issues such as algorithmic social biases (Bolukbasi et al., 2016), the idealized and pragmatic economic uses of AI (Srnicek, 2017), and the consequent reproduction of already existing power structures by predictive models (Crawford, 2021) have been problematized in the literature. This paper asks what kinds of data and labour mobilization occur in and around the production of predictive models: What political economy and socio-technical conditions are involved in the production of AI? How do these conditions produce predictive models that shape our sense of self and identity? Focusing on Kaggle, a platform for crowdsourcing AI development, I use digital methods and a software studies approach to examine the practices of the data science community on three high-profile machine learning projects and conclude by arguing that machine learning has been thought of and developed as a prediction of the self in order to prescribe individual behaviour to fulfill specific economic conditions.
Presentation 4
The elite among users: Identity formation of vendors and customers on darknet drug trade sites
Piotr Siuda
Kazimierz Wielki University in Bydgoszcz, Poland
This study delves into the digital identity formation of vendors and customers on darknet drug trade sites, focusing on Cebulka, the largest Polish-language cryptomarket. Recently, we have seen a rise in interest in studying online drug trade. Despite this growing attention, research on how individuals present themselves online and construct their identities in dark web environments remains relatively scarce. Through a dual-stage methodology combining conventional content analysis (CCA) of 8170 posts and in-depth interviews with users (n=10), this study explores how Cebulka’s users curate their online personas. The findings reveal that vendors employ sophisticated marketing strategies, emphasizing product quality to build brand identity. Consumers, in turn, contribute by sharing detailed feedback. All these practices foster a community of informed users who view themselves as superior to traditional street-level traders and clear web (social media) users. This self-perception extends to a belief in their enhanced knowledge and quasi-expertise concerning drugs, a distinction from conventional drug users, and a separation between their online and real-life identities. The study illustrates that these digital personas are collectively shaped, drawing on social identity theory and performance theories to understand the platform’s behavior and interactions. This research not only bridges a gap in understanding the complex dynamics of darknet drug trading but also offers insights into the broader subculture of drug users, suggesting distinct identifications and identities among those active on the dark web. It challenges traditional views of drug traders and has implications for harm reduction and policy development.
