Randomly generated content poses problems for theories of digital art: such content is resistant to structural theories, which can only provide templates, and one cannot assume a shared text for close analysis. Instead of reaching fixed endings, such works also tend to be of indefinite length or at least suggest indefinite possible combinations. I argue that the impact of such works can instead be found in how one attempts to work through their underlying grammar, based on limits in the algorithms that generate the content — not those limits themselves, but how their outlines come to be known. Repetitively iterating through these works simultaneously upholds the chance nature of the epiphenomenal occurrences while also illustrating the sameness of the underlying algorithm over time, creating a future-oriented interpretive arc. I examine two works that play off of this technique in different ways: Nick Montfort’s Taroko Gorge, a poetry generator which uses random generation to distill the essence of its object’s possibility, and the action role-playing game Torchlight, which attempts to elevate chance beyond a mere gameplay mechanic and toward an ethic.
(Author's abstract at DHQ)