Fastcompany has just published a profile of Robin Hauser Reynolds and her work on the forthcoming documentary CODE: Debugging the Gender Gap (which recently made a stellar fund-raising debut on Indiegogo). I met with Reynolds recently to film some material for CODE. This is going to be important and I expect influential film. Keep your eyes out!
The Fastcompany piece refers favorably to The Computer Boys Take Over, and mentions my work on the Computer Girls article from Cosmo.
Academic books do not usually attract the attention of the general public, much less Hollywood celebrities. But after reading this fascinating interview with the actor Gillian Jacobs (Community, Life Partners) about her forthcoming Grace Hopper documentary, I tweeted the following quote:
GJ: I not only want to tell people about Grace Hopper, but remind them that she was not the only woman in her field in her era. Women have always been a part of tech and computing.
Imagine my surprise when I received the following reply!
The much-hyped and controversial website Vox.com (“Its mission is simple: Explain the news”) has been taken to task for a recent article claiming that the speed of adoption of new technologies has been speeding up. They have been criticized not only for their uncritical and misleading use of data, but also the way in which they approached the process of making corrections to the original article.
The actual claim made in the Vox.com piece about the supposed accelerating pace of technology is not at all original. In many ways, it would be hard to find a more conventional piece of “wisdom.” It is true that their reliance on Youtube videos allegedly showing how children today cannot figure out what a Sony Walkman might be for is particularly anecdotal (“kids say the darndest things!”), but if you were to ask the proverbial man or woman on the street about technology this is pretty much exactly what they would say.
The Vox.com article is a prime example of what I teach my students about the dangers of the “s-curve.” The s-curve has become something of a cliche in pop-economics writing about the history of technology.
Here is the basic form (and premise) of the s-curve graph (adapted from a recent lecture in my Information Society course):
The idea is that the adoption of a novel technology often starts slowly, then accelerates rapidly as the technology gets perfected, and then tails off as the technology becomes mainstream. The “fact” that the length of these s-curves are getting increasingly shorter is the premise behind many a “technology is driving history” argument — including the recent one made by Vox.com.
The problem, of course, is that by fiddling with dates, scale, or detail, you can fit any technological phenomenon into a convenient s-curve.
Consider for example this illustration of the adoption of electric-car technology:
In the surface, this seems to capture the s-curve phenomenon neatly.
But let us provide a more historically-accurate graph of electric-car ownership in the 20th century, which actually looks more like this:
The really interesting phenomenon here is how popular electric cars were in the early decades of the 20th century. Here is a close view of that period. Notice that ownership peaks at about 1920.
Here is a picture of an Edison manufacturer electric car from this period
and, just for fun, a picture of Colonel Sanders standing next to his electric car
The point is that these vehicles were popular. It was only a combination of social changes (electric cars get gendered female — they become known as “chick cars,” so to speak), technological innovations, political changes (cheap oil!), etc., that gasoline powered vehicles become standard. [For more on this history, see David Kirsch’s The Electric Vehicle and the Burden of History]
If we overlay a graph of the adoption of hybrid gas-electric vehicles onto this history, we can begin to explain the resurgence of electric vehicles in the early 21st century. (Again, the explanation is social, political, and technological).
Finally, we could overlay all of this with an s-curve that seems to neatly capture the phenomenon. But this would provide an entirely false picture of the history of the electric car, and would suggest a coherence to the s-curve model of technological adoption that is entirely inconsistent with reality. The story of the electric car is not one of gradual (albeit slow) transformation from niche to mainstream technology. The s-curve does not fit.
So how does this relate the the Vox.com article?
Depending on how you chose your endpoints, you can always construct a picture of accelerating adoption. Take for example the curves associated with various music reproduction technologies:
This seems to support the idea that the adoption period of the iPod was much shorter than that of the phonograph. This is probably true. But what does it tell us? If we think more broadly about the underlying phenomenon, which is music reproduction, we get a different story.
Yes, consumers took to the iPod much more quickly than the Sony Walkman. But this is because the Sony Walkman had already done all the work — social, economic, etc. — that accustomed people (and music publishers) to the idea of portable, mass-reproduced popular music. And the Sony Walkman in turn was building on decades of work — again, social, economic, and legal — that had already changed the way in which Americans consumed music. What do you think was the more revolutionary moment of technological change? When you upgraded your Walkman to an iPod? Or when your grandparents first heard recorded music on a phonograph? It seems pretty clear to me that the latter was the much more significant (and disruptive) experience.
How does this relate to the history of computing? My lecture on “dangerous s-curves” was created specifically to talk about the adoption of electronic digital computing technology, and in particular the personal computer. It is easy to interpret the history of the PC as a part of a “changing pace of technology” argument — but only if you ignore the many decades of technological and social work that went into create the tools, user-base, and technologies (particularly software) that made it easy to adopt this “new” technology.
The s-curve for “computing” subsumes a number of related but quite different curves (and technologies) that cover the rise — and fall — of the main-frame and mini-computer. The PC was not just the latest in a series of developments in computing. In many ways, it came out of a very different technological trajectory.
The point is, again, that you can force this history into a s-curve that supports whatever argument you want about the course and pace of technological development. But to do so conceals much more than it reveals.
Somehow I missed this review of The Computer Boys Take Over in the Digital Humanities Quarterly. Here is the money quote praising the book:
Nathan Ensmenger’s book is an impressive and engrossing historical work. He brings the crises and the peopling of computer programming alive. His historical artifacts become characters and a full picture of what this heterogeneous history looks like emerges. He adeptly weaves together competing voices in history with competing personalities to leave us with this haunting and antagonizing last line, echoed from the rhetoric of programming as created by the history: “almost thirty years after the NATO Conference on Software Engineering many programmers are still concluding that ‘excellent developers, like excellent musicians and artists, are born, not made'” [243].
But as tempting as it is to only highlight the positive from this review, I was also intrigued by the author Trisha Campbell‘s biggest critique:
And therein lies my only problem with the book, and it is my same problem with many academic books; the thing is socially constructed and the pages of the text helped us get there, but how do we build from this heterogeneity. Is there a method? Perhaps this will be Ensmenger’s second book.
Alas, I suspect that it will take me longer than that (and perhaps a couple more books) to figure this one out, but I increasingly share Campbell’s call to make the theory of social constructivism more practically applicable. One of the welcome benefits of having moved from a history of science program to a School of Informatics and Computing is that I interact more regularly with scientists and technologists. When I am talking with fellow humanists and historians it is (too) easy to wave away challenging questions by invoking theory; with practitioners, I have to work more to make myself clear, to figure out what I actually mean, and to be relevant. This is a good thing.
Slate.com recently published an interesting article by an Indiana University graduate who in 1966 created Project Flame, an early “computer” dating service. Students would fill out a punch-card questionnaire, but were not actually matched using a computer. Instead, he and his friends randomly shuffled the cards together to provide the illusion of computerized expertise.
Although Project Flame might have been a fraud, 1966 was a formative year for computer dating. The article referenced above from Look magazine describes Operation Match, a computerized dating system developed by two Harvard undergraduates, Jeff Tarr and Vaughn Morrill.1Gene Shalit, “New dating craze sweeps campus … boy …girl … computer”, Look Magazine, February 22, 1966 Within a few months, Operation Match received 8,000 applicants from nearby universities and colleges, 52% of whom were women. (Like early Facebook, the target audience was the Ivy League and associated schools: Harvard, Yale, Vassar, Amherst, William, Mount Holyoke). Within nine months, Tarr and Morrill had attracted 90,000 applicants and grossed $270,000, all using rented computer time. An alternate system called Contact was started at MIT by David DeWan. His system drew 11,000 applicants.
Interestingly, the Look article ends by talking about the need for mutual deception within the computer dating environment:
Boys have discovered that there is more to getting the girl of their dreams than ordering a blonde, intelligent, wealthy, sexually experienced wench. They must also try to guess what kind of boy such a girl would request, and describe themselves to conform to her data. The future suggests itself: the boy answers artfully. A girl does took. The computer whirs. They receive each other’s name. Breathlessly, they make a date. They meet. They stop short. There they are: Plain Jane and So-So-Sol. Two liars. But they are, after all, exactly alike, and they have been matched. It is the computer’s moment of triumph.
After a flurry of media coverage of these and similar systems, the computer dating fad of the mid-1960s seems to have quieted down quickly.2Russell Baker, “Automation Comes to Love: Computerized Mating, New York Times, Feb 10, 1966
By the early 1970s, the focus had turned to the dark side of computer dating, including fraud, misrepresentation, and violations of privacy.3 Steven Roberts, “Often, Computers Spoil Cupid’s Aim,” New York Times, Dec 25, 1970
Perhaps the most bizarre twist from this period was a Times Square bookseller who used its customer data to start its own computerized dating service — without their customer’s knowledge. They set up a dial-a-date service advertising “Girls Galore.” Women who found themselves besieged by calls from strangers experienced “anxiety and fear.” The first example of computer-related stalking, perhaps?4 “Stores Sell Names Of Women Using Dating Computers,” New York Times, Jul 30, 1968
UPDATE: an obvious question to ask about computer dating in this period is “why 1966”?
The short answer to this question is that this is the late 1960s was the heyday of the computer utility. These were services that allowed users to rent time on a shared mainframe computer, generally via a remote terminal. The practical upshot was that entrepreneurs who wanted to provide computer-based services, but who did not have the resources (or desire) to own their own computer, could rent time via a computer utility such as Tymshare, University Computing, GE Information Systems, or the Service Bureau Corporation.
The era of the computer utility was short-lived, as the difficulties associated with writing time-sharing software (see my recent post on Why Software is Hard) and competition from low-cost minicomputers demolished the revenue models of the computer utility. By these computer utilities, however transitory, represented an important moment in the democratization of computing. As one professor in the MIT School of Management described it in 1964, the vision of “an on-line interactive computer service, provided commercially by an information utility … as commonplace … as the telephone service is today” was a compelling one, and would be recreated, via the Internet, in later decades.5Martin Greenberger, quoted in Campbell-Kelly, Aspray, Ensmenger, and Yost, Computer: A History of the Information Machine (Westview Press, 2013)
In terms of the history of computer dating, the existence of the computer utilities dramatically reduced the barriers of entry into computer-based services. The sudden rise of multiple dating services in 1966 are anything but a coincidence.
ANOTHER UPDATE:
Youtube video on a London-based computer dating service (also called Operation Match)
Hat tip: Alex Bochannek
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