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of computation already widely used in human computing projects to the
new technology of the electronic computer. These plans of computation
were themselves highly gendered, having been traditionally developed by
women for women (human computing had been largely feminized by the
1940s). The ENIAC women would simply set up the machine to perform
these predetermined plans; that this work would turn out to be diffi cult
and require radically innovative thinking was completely unanticipated.
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The telephone switchboardlike appearance of the ENIAC programming
cable-and-plug panels reinforced the notion that programmers were mere
machine operators, that programming was more handicraft than science,
more feminine than masculine, more mechanical than intellectual.
The idea that the development of hardware was the real business of
computing, and that software was at best secondary, persisted through-
out the 1940s and early 1950s. In the fi rst textbooks on computing
published in the United States, for example, John von Neumann and
Herman Goldstine outlined a clear division of labor in computing—pre-
sumably based on their experience with the ENIAC project—that clearly
distinguished between the headwork of the (male) scientist or “planner,”
and the handwork of the (largely female) “coder.” In the von Neumann
and Goldstine schema, the planner did the intellectual work of analysis
and the coder simply translated this work into a form that a computer
could understand. Coding was, according to von Neumann and Goldstine,
a “static” process—one that could be performed by a low-level clerical
worker. Coding implied manual labor, and mechanical translation or
rote transcription; coders were obviously low on the intellectual and
professional status hierarchy. It was not unreasonable to expect that as
was the case in the ENIAC project, most of these coders would be
women.
To the surprise of engineers and managers at the ENIAC and other
wartime computing projects, however, programming turned out to be
much more diffi cult, time-consuming, and expensive than had originally
been imagined. What had been expected to be a straightforward process
of coding an algorithm turned out to involve many layers of analysis,
planning, testing, and debugging. For many, this unanticipated and
unwelcome divergence between expectation and reality was already a
crisis in the making. For others, the discovery of the hidden complexities
posed a stimulating intellectual challenge. For the computer scientist
Maurice Wilkes (one of the authors of the fi rst computer programming
textbook), it was a little bit of both. “It had not occurred to me that
there was going to be any diffi culty about getting programs working,”
