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ENIAC programmers, late 1940s. (U.S. military photo, Redstone Arsenal Archives, Huntsville, Alabama), from Programmed Visions by Wendy Hui Kyong Chun.

After “getting fit” and whatever else people typically declare to be their new year’s resolutions, this year’s most popular goal is surprisingly nerdy: learning to code. Within the first week of 2012, over 250,000 people, including New York’s mayor Michael Bloomberg, had signed up for weekly interactive programming lessons on a site called Code Year. The website promises to put its users “on the path to building great websites, games, and apps.” But as New Yorker web editor Blake Eskin writes, “The Code Year campaign also taps into deeper feelings of inadequacy... If you can code, the implicit promise is that you will not be wiped out by the enormous waves of digital change sweeping through our economy and society.” 

If the entrepreneurs behind Code Year (and the masses of users they’ve signed up for lessons) are all hoping to ride the wave of digital change, Wendy Hui Kyong Chun, a professor of Modern Culture and Media at Brown University, is the academic trying to pause for a moment to take stock of the present situation and see where software is actually headed. All the frenzy about apps and “the cloud,” Chun argues, is just another turn in the “cycles of obsolescence and renewal” that define new media. The real change, which Chun lays out in her book Programmed Visions: Software and Memory, is that “programmability,” the logic of computers, has come to reach beyond screens into both the systems of government and economics and the metaphors we use to make sense of the world.

“Without [computers, human and mechanical],” writes Chun, “there would be no government, no corporations, no schools, no global marketplace, or, at the very least, they would be difficult to operate...Computers, understood as networked software and hardware machines, are—or perhaps more precisely set the grounds for—neoliberal governmental technologies...not simply through the problems (population genetics, bioinformatics, nuclear weapons, state welfare, and climate) they make it possible to both pose and solve, but also through their very logos, their embodiment of logic.” 

To illustrate this logic, Chun draws extensively on history, theory, and detailed technical explanations, enriching cursory understandings of software. “Understanding software as a thing,” she writes, “means engaging its odd materializations and visualizations closely and refusing to reduce software to codes and algorithms—readily readable objects—by grappling with its simultaneous ambiguity and specificity.” Indeed, Chun spends a lot of time specifying computer terms. What's the difference between hardware, software, firmware, and wetware? Source code, compiled code, and written instructions? What is a thing and how did software become one? Even for a fairly nerdy computer user there’s a lot to pick up on. The book really shines, however, when Chun waxes poetic on the more ambiguous aspects of software. 

The term “vaporware” refers to software that’s announced and advertised but never actually released for use, such as Ted Nelson’s infamous Xanadu project. Vaporware is problematic when it comes to theory because grand ideas and slick renderings rarely (if ever) align with the way technology looks and works in real life. Geert Lovink, Alexander Galloway, and others have called to banish “vapor theory,” theory built on hypothetical ideas about software rather than instantiations of it, which Lovink criticizes as, “gaseous flapping of the gums...generated with little exposure, much less involvement with those self-same technologies and artworks.” Chun concedes that while this embargo on vapor has been essential to grounding new media studies, “a rigorous engagement with software makes new media studies more, rather than less, vapory.” Vapor is not incidental to software, she argues, but actually essential to its understanding. This is what makes Chun’s theories exciting to follow: she engages renderings, dreams, and misunderstandings about technology rather than casting them aside. The key source of these misunderstandings is the use of the computer as metaphor.

People in previous generations conceptualized the world around them using technologies like clocks and steam engines. While these analog, mechanical devices are intricate, if one were to take apart a clock and and put it back together its inner workings could be understood. Digital computers are more complex because they are made of both tangible chips and immaterial codes, neither of which are intuitive to deconstruct. Further, all software interfaces, like the “paintbrush” tool in Photoshop, are metaphors themselves. “Who completely understands what one’s computer is actually doing at any given moment?” asks Chun, knowing that the answer is nobody. Yet this murky recursion of “unknowability” and vapors is exactly why Chun finds software to be such an apt metaphor for the world we live in. Recalling Stewart Brand’s call for a picture of the whole earth in 1968, Chun poses the question: what would a picture of the whole Internet look like? Except, in this case, to find out may not be the point. In the way that the stock market is based on speculation—virally spreading fear about the future of a company (as opposed to concrete evidence or actual bad management decisions) can cause a stock to tank—a technologized world is increasingly based on conjecture. In its unseeable, untouchable, and effectively unknowable nature, the computer represents the lens we need in order to think about the enormous and incomprehensible forces of social, economic, and political power that govern our lives. “[Software’s] ghostly interfaces embody—conceptually, metaphorically, virtually—a way to navigate our increasingly complex world,” writes Chun. 

The book looks at a broad range of examples from artists, scholars, and technologists to situate “programmability” in relation to everything from global systems like capitalist economics, neoliberal politics, and knowledge production to those of the mind and body: gender, race, and the structure of thought. The footnotes are full of interesting paths waiting to be followed: Frederick P. Brooks on why programming is fun and hacking is addictive, Ben Shneiderman on direct manipulation interfaces, Brenda Laurel on computers as theatre and how that relates to skeuomorphism, and Thomas Y. Levin on the temporality of surveillance, to name just a few. While it’s tempting to look to this web of ideas and the history of computing as an answer for why things are the way they are today, Chun's point in invoking all these voices is that it’s not that clear cut.

Some of the book’s propositions about our relationship to computers seem overblown: a priestly source of power, a form of magic, code as a fetish. If nothing else, these phrases are provocative and point to how potent Chun finds software to be in the world today. As more and more people find themselves able to create things out of code, it feels critical to understand software on both a practical and fundamental level.

(Vladimir Lukyanov's water computer, 1936. Image courtesy of the Polytechnic Museum, Moscow.)

I only recently found out about Google's reverse image search functionality. Since then I've been busy feeding its search engine some of the more mysterious images that have been littering my archives for years, hoping finally to figure out what they are actually pictures of, and why I even found them interesting enough to keep in the first place.

One of those images is the one you see above. According to a translation of this article published by the Russian magazine Science and Life in 2000, it shows one of the “monuments of science and technology” that “brought [the Soviet Union] to the forefront of the analog computer” — Vladimir Lukyanov's marvelous water computer.

Built in 1936, this machine was “the world's first computer for solving [partial] differential equations,” which “for half a century has been the only means of calculations of a wide range of problems in mathematical physics.” Absolutely its most amazing aspect is that solving such complex mathematical equations meant playing around with a series of interconnected, water-filled glass tubes. You “calculated” with plumbing.

To better explain how it works, here is a description by Steven Strogatz of what I'm assuming is a comparative device. Built in 1949, nearly a decade and a half after Lukyonov's, it's called the Phillips machine, after its inventor, Bill Phillips.

In the front right corner, in a structure that resembles a large cupboard with a transparent front, stands a Rube Goldberg collection of tubes, tanks, valves, pumps and sluices. You could think of it as a hydraulic computer. Water flows through a series of clear pipes, mimicking the way that money flows through the economy. It lets you see (literally) what would happen if you lower tax rates or increase the money supply or whatever; just open a valve here or pull a lever there and the machine sloshes away, showing in real time how the water levels rise and fall in various tanks representing the growth in personal savings, tax revenue, and so on.

“It’s a network of dynamic feedback loops,” Strogatz further writes. “In this sense the Phillips machine foreshadowed one of the most central challenges in science today: the quest to decipher and control the complex, interconnected systems that pervade our lives.”

(A diagram of the Philips machine, alternatively named the “Moniac” by a Chicago economist “to suggest money, the ENIAC, and something maniacal.” Source.)

To go back to Lukyanov, his water computer was built specifically to solve the problem of cracking in concrete, a “scourge” that slowed the construction of railroads by his employer. Doing so meant developing manufacturing regimes for concrete blocks that take into account the complex relationships between material properties, the curing process and environmental conditions. Existing “calculation methods were not able to give fast and accurate solutions.” Lukyanov's invention could.

Appropriating and altering Strogatz's text, we get:

Filling up not just a corner but the entire room, inside not one but several structures that resemble large cupboards with a transparent front, is a Rube Goldberg collection of tubes, tanks, valves, pumps and sluices. You could think of it as a hydraulic computer. Water flows through a series of clear pipes, mimicking the production line of concrete blocks. It lets you see (literally) what would happen if you change the type of cement used or increase the load capacity of the concrete or whatever; just open a valve here or pull a lever there and the machine sloshes away, showing in real time how the water levels rise and fall in various tanks representing material properties, curing time, temperature, and so on.

Changes to the water level in the “measuring tube” would be marked on a graph paper — “a kind of curve,” and “these marks build schedule, which was the solution of the problem.”

Because of the simplicity of their design and programming, subsequent models were “successfully used” in other fields such as geology, thermal physics metallurgy and rocket engineering. The first and second generations of digital electronic computers could not match their computing abilities. In the mid-1970s, they were still being used in “115 manufacturing, research and educational institutions located in 40 cities” across the Soviet Union. “Only in the early 80s” were digital computers cheap, configurable and powerful enough to match the “possibility of [the] hydraulic integrator.”

(A museum display at the Polytechnic Museum, Moscow, presenting an incomplete history of computers. Photo by Mikhail Shcherbakov. Source.)

Having briefly traced the history of water computers forward from Lukyanov to the rest of the 20th century, I can't help but thread the timeline backward to include some of the most elaborate hydraulic engineering schemes used in sprawling aristocratic gardens of early modern Europe, such as the always indispensable Versailles, the hydro-acoustically drenched Tivoli, the masterworks of Salomon and Isaac de Caus, and one of my top favorite gardens, Pratolino.

Garden historians usually characterize the technical control of water in stately gardens as part of a system of social control. As an alternative, or at least to offer another layer of meaning, this augmented timeline presents a crypto-historical narrative of gardens as gigantic water computers.

(Etienne Dupérac's bird's-eye plan view of the gardens at Villa d'Este, Tivoli. Source.)

All those water-screws, force pumps, water-lifting wheels, vents, wells and settling tanks, all those reservoirs, canals, aqueducts and pipes buried under mountains and rivers, and all those jets spurting out of vases and statuaries, creating water rainbows and sonic merriment, and all those fountains, water parterres, giochi d'acqua, automatas and damp grottos: those are the gurgling circuits, the programmable interfaces, the data storage devices and the visualization screens of landscape proto-supercomputers.

To operate it, you will have to consult an unpublished edition of Solomon de Caus's Les raisons des forces mouvantes, avec diverses machines tant utiles que plaisantes, auxquelles sont adjoints plusieurs dessings de grotes & fontaines, from which the following may have been excerpted:

Embedded in the earth is a Rube Goldberg collection of tubes, tanks, valves, pumps and sluices. You could think of it as a hydraulic computer. Water flows through a series of clear pipes, mimicking the way that money flows through the empire. It lets you see (literally) what would happen if you lower the price of bread or increase the construction of palaces or whatever; just open a valve here or pull a lever there and the machine in the garden sloshes away, showing in real time how the water levels rise and fall in various tanks representing colonial trade supplies, food riots, and so on.

Attached to the measuring tube is a series of fountains that gurgles the solution to the equation.

(Jean-Baptiste Martin, Vue du château de Versailles depuis le Bassin du Dragon et de Neptune, 1700. Source.)

Gardeners and their patrons would then walk around marking the fluctuating levels of these fountains on graphic paper. From fountain to fountain, they follow a set of programmed perambulations, gathering data at relevant nodal points, along the way not just picking up the solutions to the problem being computed but also gaining a greater understanding of the complexities of the natural and social worlds.

With these gardens as crypto-water-computers, they were taking measurements of the universe.

(See also La Machine de Marly.)