and

I started in 2011 with the lofty goal of building a computer from scratch. Along the way I learned a lot about how computers work and a little about how humans do too.

Over the next 7 chapters I’d like to share my experiences, learning about the fundamentals of electricity and computation by playing with circuits, making mistakes, and finding a story that’s kept me going.

Dawn & Dusk

Why learn about computers? Because…

…but how many of us really know how a computer works?

I didn’t, so I decided to try building one of my own. A Handmade Computer that would let me see how all the pieces fit together.

There is a Silicon Valley mythology centered around protagonists like Gordon Moore, Bill Gates, and Steve Jobs, a legend of innovation which traces its history to an idealized California counterculture.

But left out of this glossy narrative are the parallel stories of militarization, state power, and mass production, which not only financed, but provided the social conditions for the computing industry as we know it.

In fact, we get the term “computer” from the forgotten practice of human computation. Well before computers became “personal,” an entire profession of arithmetic labor (mostly women) were contracted for scientific and military production.

So, understanding the computer requires study of both its essential technologies and the story behind the utopian myth. A history of grand calculating machines, built to accelerate the engines of war, and the so-called “Californian Ideology,”^{1 2} that grew out of the military-industrial complex to produce the Silicon Valley we know today.

We’ll learn all about this as we build a computer of our own, together.

However…

Life can’t be reduced to binary.

Interface

Every day we look at computer screens for a very long time. We touch them, carry them, sleep next to them. Our lives are stored in bits, messages turned to network packets. Living spaces arranged in human-sized pixels.

But behind the familiar interface, the inner workings still seem so distant. For most of us the window into our digital lives is opaque.

How did we get here? Well… as the computer was commoditized, users became the primary source of value. Commercial incentives drove corporations to establish proprietary ecosystems³ to capture market share, setting off fierce competition for “frictionless” experiences that deliberately concealed the logic inside. And with computers designed to be ever-more complex, while interfaces made ever-simpler, the gap between user and machine only grew wider.

But now we’re getting ahead of ourselves. Before we get into history let’s begin by describing the computer in simple, technical terms, as an object that performs only a few basic operations, repeated and abstracted.

Most of the time, when we use a computer, we are looking at a graphical user interface, GUI for short, that’s displayed on our monitor. And when we enter text with a keyboard or move our mouse, the interface software passes that data to a shared system which makes the information available to many applications.

The GUI software, like all computer programs, is made of code. Code is the language of the computer. Sets of instructions for how the hardware should manipulate stored information.

Once the instructions have been completed, the results then flow back to the GUI and can be seen as changes on the screen. Computed at high speed, this interactive loop quickly moves information through many levels of abstraction, the result appearing almost instantaneous to you and me.

Just like a painting, stepping inside the computer takes patience, but it may be easier than you think.

Open a computer and you find lots of small electronic components connected to a circuit board which ties them all together. This is an image of a microchip made in 1963 shown at 100x magnification.

Micrograph photos reveal the unique visual patterns of the computer’s interior circuitry. Designed to maximize performance at infinitesimal scale, they can also be quite geometrically appealing. When I look at images like this one I see dynamic works of art, grid plans for a miniature city.

Peter Halley’s painting Instant City reminds of a computer architecture diagram, information flowing from one box to the next. The painting depicts various levels of abstraction differing in size and color, but with the same essential pattern throughout.

It’s surprising how often you’ll find connections between art, architecture, and computation. The term “design pattern” for instance, used to describe a computer’s repeated software elements, was first introduced to computer engineers by the architectural theorist Christopher Alexander.⁶

Computation, abstract painting, and Modernist architecture each have their own seperate histories. But all three were affected by the same ethos of industrialization and their visual similarity reflects this shared influence.

• CPU diagrams visualize the operations and the flow of information within the computer’s hardware.
  
  
• Paintings like Instant City render geometric forms of control onto the two dimensional surface.
  
  
• City plans describe the layout and organization of urban life.

They are abstractions designed for controlled repetition: repeated signalling, repeated viewing, repeated interaction.

Repetition is a powerful tool that lets us perform complex tasks by breaking them down into a series of a simple operations. It enables a basic pattern to scale to larger, more complex structures. This process of scaling through repetition can be seen from the microscopic details of silicon chips, to the grand scale of urban development.

In the built environment there are also physical loops, infrastructures that move objects and information. At every level of urbanization, from city center to the most remote areas, space is connected through human-scale circuits. From shipping routes to telecommunication networks, the city breathes through these loops, circulating the people, material, and information that bring it to life.

Cities are made by executing urban programs. In her essay An Internet of Things,⁸ Keller Easterling argues that “activity in a spatial environment is not reliant on the digital environment. It may be enhanced by a code/text-based software, but a spatial software or protocol can be any platform that establishes variables for space as information.” The exchange of culture that flows through a city’s architecture and transportation is the software of contemporary space making. So…

While the binary computer executes programs with precision, cities are most often unpredictable, even unquantifiable. I’m reminded of Jacques Tati’s film Playtime, where the choreography of urban life unfolds as programmed chaos and serendipity. If cities are computers for humans, they run buggy software and often fail to compile.

Shannon Mattern critiques notions of the “smart city” that conflate data with memory, and decision with execution. Instead of reducing the city to a computer, she challenges us to “recognize spatial intelligence as sensory and experiential; that consider other species’ ways of knowing; that appreciate the wisdom of local crowds and communities; that acknowledge the information embedded in the city’s facades, flora, statuary, and stairways; that aim to integrate forms of distributed cognition paralleling our brains’ own distributed cognitive processes.”⁹

Perhaps some qualities of cities are uncomputable, like the unpredictability of the environment or the ungraspable nature of the human mind.

Thinking about similarities and differences between the city and the computer helps us recognize the cultural complexities that surround them. By opening the computer to look at the inner workings, we may begin to ask: what kind of computers do we want to use and what types of cities do we want to live in?

Chapter 2, Skating the Circuits →