Generative art requires an autonomous system and a degree of unpredictability

Generative art is defined not by style but by methodology: the artist creates rules and initial conditions, then triggers an autonomous process that produces the work. Two hard rules apply: (1) autonomy must be involved — the system cannot be entirely under the artist’s control; (2) there must be a degree of unpredictability — the artist can be as surprised by the outcome as anyone else. Philip Galanter’s canonical definition: ‘Generative art refers to any art practice where the artist uses a system, such as a set of natural language rules, a computer program, a machine, or other procedural invention, which is set into motion with some degree of autonomy contributing to or resulting in a completed work of art.’ The common factor of generative artworks is not style but the methodology of production. Even a programming language producing deterministic output is only generative if autonomy and unpredictability are present.

Examples

Mozart’s Musikalisches Würfelspiel assembles a minuet from pre-written sections chosen by dice rolls. Brian Eno’s Discreet Music uses a tape-loop feedback system. A 24-line Processing sketch that produces different images every run is generative; a sketch that always draws the same shape is not.

Assessment

Given a description of an artwork’s creation process, determine whether it qualifies as generative art and justify which of the two hard rules (autonomy, unpredictability) are or are not satisfied.