Calculating Knowledge: Computing, Capitalism, and the Modern University, 1930-2000

As artificial intelligence renews anxieties about the automation of intellectual and scientific labor, "Calculating Knowledge" uncovers the deeper history of these concerns. The project situates today’s debates within a longer story about the entanglement of computing, capitalism, and higher education in the twentieth-century United States. In the decades after World War II, computing technologies were framed as tools that could both transform and destabilize intellectual and scientific labor, especially through automation. Advocates of computing education and infrastructure—including federal officials, academics, university administrators, and corporate managers—believed these technologies would drive broad transformations in the US economy. Seemingly technical decisions about programming curricula or mainframe access on university campuses were, in fact, debates about the future of work in a “postindustrial” society. Universities became the primary institutions where these transformations were both imagined and enacted. They were newly cast as engines of economic growth, producers of mass education, and sites where computing skills were cultivated for an emerging knowledge-based economy. In these spaces, anxieties about automation and aspirations for economic expansion converged. By analyzing both the promises and realities of computing education, "Calculating Knowledge" demonstrates how universities functioned as laboratories for reimagining the role of knowledge in capitalism. The project argues that today’s discussions of AI and “knowledge economies” repeat, in altered form, dilemmas first crystallized in the rise of computing education—about how technology reshapes labor and the economy.