Review of John Cage's Usage of I Ching in His Compositions

A chance operation is a method of generating something independent of the creator’s will; it’s part of a generative system. John Cage used chance operations to “imitate nature in its manner of operation,” specifically using the I Ching in his compositions in the mid-twentieth century. He would use the symbol system to make chance-controlled compositions, “asking” the book questions about aspects of the composition and using the answers to work with. The most well-known of those pieces might be the Music of Changes, a piece made through applying decisions made using the I Ching to decide on charts of sounds, durations, dynamics, tempo, and densities.

He and Marcel Duchamp, another artist, made use of chess and chance operations. Together they filmed “Marcel Duchamp and John Cage,” a document of a chess game between the two, using a semi-random arrangement of camera placement, focus setting, and length of shot; those used chance operations. He also filmed a movie of a game played by Cage and Teeny, Marcel Duchamp's wife.

In general, chance operations can be used to make any work of art through taking the decision out of the maker’s hands. Every possibility should be associated with a result; for instance, a dice could be rolled, and depending on the number result, the artist would select a particular color. Or, as in the case of Cage, the I Ching could be consulted to specify attributes of the artwork, carried out by human hands. In the case of computational art, in some cases the human only needs to set the stage, and chance operations can be carried out by a computer.

Wolfram’s classes of behavior pertaining evolutionary automata divide cellular automata into four classes. The 2nd class is that of periodic, alternating patterns; repetitive, and ultimately predictable. One example of this in the real world is the revolution of the earth around the sun, denoting our years.

A complex and purposeful pattern which is not necessarily repetitive belongs to class 4 of the classes of behavior. One such pattern is human thought; our thoughts are often purposeful, hopefully complex, and while sometimes we do repeat ourselves generally each thought is new and part of a complex train of thought or stream of consciousness.

An example of a computation in the world that is feasible but unpredictable is the creation of a person’s work of music. We can know the possible notes, ranges, instruments, tempos, and such, but even knowing almost all possible components, it is implausible to predict the end result of someone composing a piece of music, or, along the same lines, another work of art.

Emergent behavior is what happens when complex behaviors emerge from individual entities obeying small rule sets and interacting with one another. My own understanding of it is that it is when many tiny actors/beings create something that appears greater than the sum of its parts; each individual follows strict rules, but the result can be surprising and unanticipated.

One example of emergent behavior that we examined in class is that of biomorphs, the term coined by Richard Dawkins. Specifically, a popular offshoot of that idea was the implementation by Roger Alsingof ‘evolving’ the Mona Lisa from mere polygon shapes. This was a sort of evolutionary programming technique wherein basic algorithms could take individual units and evaluate their relative fitness, only allowing the ‘most fit’ parts to survive. Thus, over time, something very akin to the Mona Lisa would emerge.