CONCEPT
Inductive Statecraft
Fourcade and Gordon's 2020 term for the AI-era mode of governance in which categories are discovered in data rather than imposed from theory — an apparent solution to
Scott's legibility problem that turns out to be its more sophisticated reproduction.
Classical
high modernism required the state to impose simplification on complex realities — to flatten the land into a cadastral
grid, to sort the population into census categories, to organize the economy into measurable sectors. AI-era governance, by contrast, can let simplification emerge from data: categories are induced from patterns rather than imposed from above. The algorithm does not need to define risk categories in advance; it discovers them in the data. Marion Fourcade and Jeff Gordon's concept of
inductive statecraft names this mode of governance and captures both its
promise and its peril. If categories emerge from reality rather than being imposed on it, surely they capture more of reality's complexity? The appearance is deceptive. The categories that emerge from AI analysis are still simplifications — still reductions of complex, contextual, local reality to patterns that the system can process. They are more sophisticated simplifications than the cadastral grid, but they are simplifications nonetheless.