Communications of the ACM
Dynamics of Gender Bias in Computing
Credit: Andrij Borys Associates, Shutterstock, Robert Scoble/Flickr
In May 1948, women were strikingly prominent in ACM. Founded just months earlier as the "Eastern Association for Computing Machinery," the new professional society boldly aimed to "advance the science, development, construction, and application of the new machinery for computing, reasoning, and other handling of information."36 No fewer than 27 women were ACM members, and many were leaders in the emerging field.a Among them were the pioneer programmers Jean Bartik, Ruth Lichterman, and Frances Snyder of ENIAC fame; the incomparable Grace Murray Hopper who soon energized programming languages; Florence Koons from the National Bureau of Standards and U.S. Census Bureau; and noted mathematician-programmer Ida Rhodes.26 During the war, Gertrude Blanch had organized a massive human computing effort (a mode of computation made visible in the 2016 film Hidden Figures47) and, for her later service to the US Air Force, became "one of the most well-known computer scientists and certainly the most visible woman in the field."24,25 Mina Rees, a mathematics Ph.D. like Hopper and Blanch, notably funded mathematics and computing through the Office of Naval Research (1946–1953), later serving as the first female president of the American Association for the Advancement of Science. In 1949, Rees was among the 33 women (including at least seven ACM women) who participated in an international conference at Harvard University, chairing a heavyweight session on "Recent Developments in Computing Machinery."29
Key Insights
Their prominence has led to the widespread but inaccurate impression that women were numerically dominant in early computer programming. As one account puts it, "at its origins, computer programming was a largely feminized occupation."18,19 This view, resting on suggestive but fragmentary data, has become prominent in popular culture, scholarship, and mass media, including the Wall Street Journal and National Public Radio and the widely acclaimed 2015 documentary "Code: Debugging the Gender Gap" by Robin Hauser Reynolds.14,41 The film popularized the conjecture by some scholars that "women made up 30% to 50% of all programmers" in the 1950s or 1960s and that male programmers subsequently pushed them out. Porter writes, "By the 1960s, women made up 30% to 50% of all programmers, according to [historian] Ensmenger" (specifically citing the Robin Hauser film).46
Comments
CACM Administrator
[[The following letter and response are published on the Letters to the Editor pages of the August 2021 CACM (https://cacm.acm.org/magazines/2021/8/254319).
--CACM Administrator]]
Thomas J. Misa's "Dynamics of Gender Bias in Computing" (June 2021), judging that the composition of the programming workforce before 1970 has been mischaracterized, overlooks important sources in establishing a valid workforce composition "starting point." The article looks at SHARE (IBM "scientific" users), CDC Coop (CDC 1604 "scientific" users), UNIVAC USE (UNIVAC 1100-series "scientific" users), Burroughs CUBE (mostly Burroughs 5000 "scientific" users) and Mark IV (Informatics Mark IV utility users of IBM "business-oriented" machines) user groups as a basis for estimating the proportion of women programmers in the programming workforce. Even after assigning weights to these numbers according to installed computer base, the great weight given "scientific" installations invalidates their use as a representation of the total work force. If user groups are a valid source, IBM GUIDE and COMMON for "business-oriented" users must be included. There were far more "business-oriented" installations than "scientific" installations. Installed computer base was reported monthly in the early days of Datamation magazine and issues are available at the Computer History Museum.
Civilian and military "business-oriented" data processing departments already existed in significant numbers before the first computers were sold. They were filled withmostly IBMCAMs (punched card accounting machines), programmed with wired plugboards. Programming was complex; in 1955 I took an intensive six-week introductory course in the Air Force. In military and civilian businesses these machines were handled and programmed by male high school graduates. They were as skilled as automobile mechanics but happened, upon graduation, to take their first job in an office rather than a repair shop. "Business-oriented" computers were usually introduced into shops that already had PCAM-based data processing departments. The natural source of programmers was the pool of plugboard wirers who understood the existing applications and their PCAM process, and understood their old machines and were not in awe of their new ones.
An interesting study of "business-oriented" first-generation computers and their programming would look at USAF Air Materiel Command, headquartered at Wright-Patterson AFB, Dayton. AMC was probably the biggest single user of first-generation computers in the U.S. Their larger depots used large-scale IBM 702s and 705s. Smaller depots used IBM 650/RAMACs, which were complex configurations for their time. The depots were staffed mostly by civilians who, I assume, fit the profile of "business-oriented" programmers I described.
Ben Schwartz
Brooklyn, NY, USA
AUTHOR'S RESPONSE:
Thanks to Ben Schwartz for pointing out IBM GUIDE and COMMON to fill out "business-oriented" users. Additional diverse user groups would enrich our understanding. I now believe researchers should sum gender probabilities and not merely tally men's and women's names, since names change gender. See names in Mattauch et al.(1): 'Johnnie' born in 1925 has 0.39 probability of being female; but 0.17 if born in 1975 (Social Security Administration data). Same years, 'Leslie' switches from p (F)=0.08 to 0.86. There are plenty of accomplished computer science Leslie's, both genders, that should be accurately identified.
Thomas J. Misa
Lopez Island, WA, USA
REFERENCES:
(1.) Mattauch, S. et al. A bibliometric approach for detecting the gender gap in computer science. Commun. ACM 63, 5 (May 2020), 7480; https://doi.org/10.1145/3376901
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