Good learning environments, Kay argues, “make contexts visible, make them objects of discourse and make them explicitly reshapable and inventable.”
In ancient Latin, a calculus was a small stone used in counting, arithmetic (an abacus bead), gaming (a token), and voting. Pebbles helped people to play, think, calculate, negotiate, and reason. The word evolved to refer to reasoning and computation (calculate), mathematics (calculus), and the people and machines who calculate (calculator).
The architecture of nature, in other words, is self-similar. It is ripe with potential analogy. This may also be so because, as some cognitive scientists contend, the core of human cognition is analogical. We see analogies everywhere, in other words, because analogy is how we think. Nature rhymes because we’re wired to hear it that way. As a result, natural analogies abound, awaiting discovery, and engineered analogs await contrivance.
Housing shortages motivate a city to approve development. But builders need time to secure financing, and construction takes time (latency). As housing costs go up, people might move to another state. By the time new homes are ready, housing may already be in oversupply, especially if speculators caused overdevelopment (leading and inertia). A boom-and-bust business cycle may be nothing more than hunting behavior—oscillation around a desired goal.
Turing’s universal machines, given a paper tape that described any other automatic machine, could simulate that machine. When realized as an actual machine, this entailed an ontological flattening: the external patch cables that configured a machine like ENIAC were moved inside the device’s memory—onto the paper tape, as it were.
Constructionism held that children learn best when seeking knowledge for their self-motivated projects and that they should be scaffolded “morally, psychologically, materially, and intellectually in their efforts.” The best way to learn French is not in a foreign-language classroom, but to live—or even better, grow up—in France. In this vein, Papert argued that microworlds offered a chance for people to live in “Mathland”—or any number of lands. (Children, of course, could build their own microworlds.) Computers, through their incredible power to simulate, could conjure whole worlds—tangible representations that suited a child’s interests, culture, and embodied experience.
Like sidewalk curb ramps—which benefit everyone, not just people with disabilities—designing a computer for children vastly expanded the potential reach of computing.
There was a hitch with completing the C64 version: Wright had lost its human-readable source code. All that remained was the compiled program binary, a long, cryptic sequence of numbers. In order to emblazon “SimCity” on its title screen they resorted to editing the compiled binary with a bitmap editor. It is for this reason that the C64 release is historically important. Like an insect trapped in amber, it depicts Wright’s City Planner before it blossomed into SimCity.
What if the profoundest kind of intelligence wasn’t to be found in playing chess, but simply walking around your home, making breakfast, or cooperating with other people in the world? Once upon a time, such social and domestic activities had been overlooked by researchers, most of whom were mathematically inclined men. To those who cherished abstract symbolic reasoning, Chess was a fine measure of intelligence, but perhaps, in the final analysis, embodiment posed the most profound challenge of all. Researchers turned to biological systems for guidance, and models of intelligence became more embodied, bottom-up, and socially situated.
In the end, it was a passionate kiss between two simulated women on the testosterone-packed 1999 E3 show floor that helped rescue The Sims from oblivion. This demo, moreover, arrived at a moment of spiraling concern over violent entertainment—games like Doom were linked to a tragic spate of US school shootings, and the ensuing moral panic probably helped create an environment more receptive to The Sims.
As in a fairy tale, Braun fulfilled his wish for a publicly traded company, but this had unforeseen consequences. As Maxis took on investment, its appetite for the kind of long-term risks that had made SimCity possible in the first place soured. The WP investment extended the reach of the SimCity network but also curtailed Wright’s autonomy and his ability to secure resources for The Sims. That Wright was expected to produce company-sustaining hits without any administrative authority points to the oddity of his Maxis identity; his business cards said “Llama Consultant,” but in SEC filings, he was Maxis’s “Chief Technical Designer.”
Looking back, Wright compared the CD-ROM to a meteor hitting Earth—an extinction-level event heralding profound changes. CD-ROM titles emphasized data-heavy multimedia, not the algorithmically rich systems he loved. Computers became faster and cheaper, and consumers developed a taste for multimedia, 3D graphics, and the Internet. It was like a meteor shower, with the competitive environment transformed over and over. The days of a single developer producing a hit were gone.
We believe power plants should be connected to the power grid, and indeed the simulation supports that belief. Summoning our expectations about power grids, the simulation requires that the first plant be connected, and so we continue to do so for the second and third—even though this is not necessary. A seaport suggests the sea, and so we place it on the shore—even though the citizens and ship are indifferent to its location. We happily remain in the dark, imaginatively filling in the details, a process Janet Murray describes as “the active creation of belief.” SimCity implies and we simulate. All of this highlights the extent to which we dine on the expectations we ourselves bring to the simulation table, and the artful setting of that table. The active creation of belief doesn’t just forgive simulation shortcomings; it underpins the entire enterprise.
According to Wright, “there are certain things we just cannot simulate on a computer, but on the other hand that people are very good at simulating in their heads. So we just take that part of the simulation and offload it from the computer into the player’s head.”
Play is simulative: not-play is transformed into play, and this transformation is marked by characteristic stylizations: reversal, ritualization, parody, schematization, exaggeration, absurdity, and paradox. These stylizations also have a metacommunicative function: they help players coordinate and signal that this is play, as when dogs perform play bows and nip rather than bite, or when people smile, make silly faces, or give knowing looks.
This bottleneck captured the interest of von Neumann, who collaborated with ENIAC’s architects on a successor design, called EDVAC, which introduced a radical idea informed by Alan Turing’s work: the computer’s electronic memory would store not just the data (e.g., numbers) of a computation but the programming itself. Storing programs in memory allowed them to be quickly loaded, modified, and stored—like any data. A program was no longer a tangled mass of wires but a mercurial pattern of bits—stored in a machine adept at manipulating such patterns. Programs could be swiftly read in from punched cards. Shape-shifting would now be as fast as any other electronic operation, and programmers would compose symbols rather than patch cables.