Concepts in Generative Art, Data as Art and Computational Aesthetics
(originally published for SFSthetik, May 21, 2013)
by Mark Gould
It seems that the genre of generative art is both growing and becoming more sophisticated every day, and receiving a lot of attention in the art press and in related social networks. But there remains substantial confusion over the term, which I hope to do my part in helping to at least clear up some of the misconceptions and clarify just what is meant by the term and what many generative artists are doing. Needless to say this will be a broad overview and probably the first of several articles on this important genre of mostly, computer related art.
Generative art refers to any art practice where the artist creates a process, such as a set of natural language rules, a computer program, a machine, or other procedural invention, which is then set into motion with some degree of autonomy contributing to or resulting in a completed work of art.
Philip Galanter
Galanter is often quoted and teaches generative art at Texas A&M University, is an artist, theorist and curator. Note that Galanter’s definition stresses that a computer by itself is not essential to generative art, although most of the generative work done these days just so happens to be done on a computer. Another definition of generative art is work that is derived from a process or processes, often but not strictly by the use of a computer, to define rules by which such artwork are produced. This can include the process of recursion, but generative art should not be viewed as limited only to the principles of recursion. Recursion, programmatic visualization and dynamic narrative are all unique aspects of computer generative art.
Since the term “computer generated” has been around for quite a long time it may cause some confusion among the general public hearing the term generative — what’s the difference? Isn’t all art created on a computer generative? Well, in a word, no. Simply put, computer generated is different than the concept of generative art, which again, has more to do with the underlying process, usually having to do with code or an algorithm in some repetitive way in the creation of the work. The generative concept has been used for many years before computers in the field of music. The fugues of J.S. Bach could be considered generative, in that there is a strict underlying process that is followed by the composer. Mozart’s Musikalisches Würfelspiel (Musical Dice Game) was an early example of a generative music system.1 Composers such as John Cage and Brian Eno have used generative systems in their works.
To many of those people both working in the field and who have either theorized about generative art seem to generally agree that the term is at some level conceptually similar to algorithmic art, which is a term that has been around much longer. So have terms like fractal art and now, procedural art. At the same time, a lot of people don’t like to get bogged down in specific terminology. Brian Eno, whose work among others has been fundamental in the fields of ambient arts and generative arts, says, “I try to stress the idea of a drawing that is the result of a collaborative process between me and the machine. Analyzing data to extrapolate data, as it applies to real human relationships, is art as much as science. And it is very specifically a collaborative process between me and the machine. Generative art may hold the clue to effectively using that data; the inspiration for computing processes that solve problems social network analysts don’t yet know that we have. (It may not, but my hypothesis is that is does.)”
It’s an interesting personal footnote that along with a lot of other people discovering computer graphics, art and design in the 1980′s, one of the the joys and realizations I had about the computer as a new tool was the power it had in the ability to allow me to do almost countless iterations on a concept that would have been difficult or nearly impossible with other tools. I felt the same way Eno does about there being a collaborative process between myself and the machine; today, computers are exponentially so much faster the iterative process feels that much more like I’m working through an idea so fast that the computer is suggesting a version or idea I wouldn’t otherwise have thought of. What others might far more simply call a happy accident!
It’s been pointed out that this is the era of “Big Data” and while Internet versions 1.0 and even 2.0 were somewhat static, the evolution and ease with which databases can be hooked into a variety of inputs and outputs has made all sorts of new things possible, live and in real time. One of the more “out front” trends in the development of live databases is data visualization. Data visualization is exciting to professionals in any number of fields because of the obvious value it has in being able filter and analyze huge amounts of real time data through some type of user interface designed to visualize that data in a much more sensible way than you ever could by just looking at the data itself. The most widely known type of data visualization might be television election night graphics, and other kinds of data visualization have been used by graphic designers for quite a while now. But now we are experiencing an explosion in this field. In the art world the potential for using data, either real or imagined, as the underlying tool for creative work along with some type of generative process appears to be what is creating this new level of explosive growth in the 21st century going forward. -MG
