The Targeting Machine

This book examines how data analytics platforms coproduce surveillance targets across four securitising assemblages in the United States and China. By comparing the Integrated Joint Operations Platform in Xinjiang, Palantir’s platforms deployed by Immigration and Customs Enforcement, the New York Police Department’s Domain Awareness System, and Huawei’s Safe City infrastructure in Shenzhen, it traces how surveillance targets emerge within longer-term colonial contexts, are contested across executive, administrative, and operational discourses, are partially stabilised by platform-mediated standardisation, and become encultured into routine agency practice. Drawing on leaked police databases, litigation transcripts, and vendor documentation, The Targeting Machine argues that analytics platforms mediate this coproductive sequence. They partially stabilise fragmented discourses of who counts as an appropriate target, without fully displacing the operational discretion that continues to shape who is actually repressed. Deploying a Wynterian theoretical framework, it further argues that platforms do not merely sort individuals into administrative categories, but demarcate which ways of living count as fully human. Finally, the book assesses each assemblage’s resulting repression capacity across organisational, data-fusion, and coercive dimensions. In doing so, it finds that the selectivity of coercive activities is not predicted by regime-type or platform design, but is instead informed by executive pressures and legal constraints.