The State's Politics of "Fake Data"
New research shows how 'fake' government data is a deliberate bureaucratic tool.
Deep Dive
A new study analyzing state data-making in China and the US argues that 'fake' data is often created intentionally to serve organizational needs, not due to failure. Researchers identified four key moments—creation, correction, collusion, and augmentation—where bureaucrats prioritize what data *does* over what it represents. They conclude that data fakeness is relational, processual, and performative, urging a shift from chasing perfect accuracy to making these 'useful fictions' accountable.
Why It Matters
This challenges core assumptions about AI training data and government transparency, impacting how we trust official statistics and datasets.