Data Entry, Labor Identity, and Inequality in Computer Automation

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This history of technology research project focuses on computer automation with an eye towards providing historical lessons for contemporary developments in artificial intelligence and robotics technologies, which are expected to uproot the balance between human and machine labor. When modernizing corporations first began installing digital electronic computers, it became clear that large amounts of information had to be converted from paper into computer-legible form before they could be processed automatically. Computer automation thus created a rapidly ballooning need for data entry, much of which was done manually. The outcomes of this project will make menial data entry a visible part of the history of computing by addressing pertinent questions such as: How did computer automation change work processes? Who took up the newly emerging routine data entry work, under what conditions, and why? In addition to funding scholarly research and publications, the project provides undergraduate student training opportunities in public history and creates a virtual exhibit that engages broader audiences with questions raised by the history of data entry about work processes and technological change today. Focusing on banking automation in the United States, West and East Germany from the 1950s to the 1970s, this project investigates computing technology and inequality at the height of the Cold War. It examines changes in the participation and identity of data entry workers and their work conditions; in addition, it raises questions about social and economic implications from bank automation, and the effects of competitive pressures on banking services for marginalized communities. Methodologically, the project supplements archival research and professional technical records with an analysis of popular magazines, newspapers, and oral history interviews to circumvent current limitations of archival collections. For the history of computing, the project shifts attention from professional—mostly male and white—programmers to unskilled data entry typists, countering linear narratives of technological progress. A transatlantic comparison will serve to provide a localizing corrective to generalizing assumptions about worker identity and technology in different political economies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.