Abstract

Over the past decade, the widespread investment in digital infrastructure and the extensive digitization of individual behaviour have provided the basis for the rapid development of machine-learning techniques and Artificial Intelligence (AI). AI datafy our body and our identity, producing live databases full of calculated linkages between humans and nonhumans. It creates a new cartography of biopower that sometimes produces technologies, but always produces subjects. This research examines the political economy of subjectivation in the “making of” machine-learning algorithms and AI by closely examining the relations of power, affect, and subjectivation on Kaggle, the world’s largest data science community. Conceived as a gamified platform for crowdsourced machine-learning challenges, Kaggle is a networked public where users are under constant pressure to produce new and improved algorithms.

This research first engages with Kaggle as a company and platform, offering a narrative of its history and a detailed description of how it works. Combining discourse analysis, software studies, and digital methods, this research aims to understand how code, data, digital infrastructures, crowdsourced labour, and political-economic interests are mobilized to create instruments of control that shape, modulate, and mediate individual behaviour. This phenomenon, which I call modes of automatic subjectivation, points toward the possibility of using subjective and impersonal materials to reorganize life in its broadest sense according to a specific system of power and privileges involving gender, race, sexuality, and social class.

This dissertation argues that these modes of subjectivation are designed to control the “production of possibilities” and reinforce specific types of socioeconomic relations, which in turn reproduce current conditions of existence. Furthermore, this research argues that the data science community has a notable compulsion toward cost reduction, indifference toward human life, an obsession with controlling populations and individual bodies, and a desire to produce a predictable future for economic gain. Ultimately, this research identifies algorithmic media based on AI Technology as a core asset in the attention economy and as a source of power that can be used as an interface to prescribe individual behaviour.