Abstract:

The rapid proliferation of generative AI models has sparked critical inquiry into the hidden precarious labour infrastructures that help sustaining their performance. This article draws on ethnographic research conducted in three Chinese AI companies to examine how the production of large-scale models is made possible through intensive, low-paid and precarious data work. It argues that AI production is underpinned by a project-based labour regime structured with insourcing, outsourcing and crowdsourcing as its main organizational forms. The regime has systematically weakened the autonomy of labor, exacerbated the instability of labor, and presented significant characteristics of labor alienation. Rather than overt resistance, workers tend to display consent and acceptance of precarious conditions. In order to conceal the essence of its labor exploitation, capital employs three main strategies of normative control to exert hegemonic power over labor in order to create "willingness" on the part of labor. This study explores how such consent is being actively produced. Gamification mechanisms reframe exploitative work as cognitively stimulating and competitive; task modularisation and fast-changing project cycles lead to cyclical deskilling, curbing worker leverage and occupational mobility; and the symbolic valorisation of AI work fosters a sense of meaning and belonging in otherwise marginal roles. These mechanisms operate as technologies of consent, embedding hegemonic control within the everyday organisation of AI labour. This paper uncovers the paradoxical reality in contemporary AI production: how capital manufactures consent to "make human work like machines so that machines can appear more human". The findings extend classic labour process theory and contribute to a deeper understanding of labour organisation and control mechanisms in the age of artificial intelligence.

Key words: artificial intelligence, projectification, precarious work, labour organisation, work autonomy