If a computer composes a symphony, should the resulting musical piece be considered a work of art? And how does a computer-generated work affect our perception of human-made works? These are not theoretical questions. A recent article in Pacific Standard highlights Simon Fraser University’s Metacreation project, which aims to investigate computational creativity, in part through the development of “artificially creative musical systems.”
This past June, three members of the project— researchers Arne Eigenfeldt, Adam Burnett and Philippe Pasquiere— presented an evaluation study of their musical works composed by software programs at the 2012 International Conference on Computational Creativity. At a public concert in which both human-composed and computer-assisted music were performed by a professional string quartet, percussionist and a Disklavier (a mechanized piano that interprets computer input), audience members were unable to differentiate between music generated by a computer and music written by a human composer, regardless of their familiarity with classical music.
The Metacreation project is not the only example of advances in artificial intelligence (AI). David Cope’s Experiments in Musical Intelligence (EMI) is a software system that analyzes existing music, and then generates original compositions in the same style. What’s more, such advances aren’t limited to musical arrangements. Marginal Revolution reports on a study that found that automated ratings of short essays by junior high and high school students did not differ significantly from human assessments of the same papers. And the Tate Gallery, SFMOMA and the Brooklyn Museum are among the institutions that have exhibited paintings made by AARON, an autonomous art-making program created by Harold Cohen. Indeed, computers’ capabilities now rival cognitive functions once thought to be intrinsically human. Computers can form links, evaluate, and even make novel works; they can function in ways that we think of as creative. So it follows, if computers are performing creatively, should we consider the resulting works art?
The simplest, and in many ways most appealing answer to the human ego is that no, these computers are not making art. Art requires intention. This is why projects like Rirkrit Tiravanija’s Untitled 1993 (Café Deutschland), in which the artist set up a functioning cafe in a private gallery in Cologne, or Lee Mingwei’s The Dining Project, in which Mr. Lee cooked and shared “foods and introspective conversation” with individual guests, are art; their makers intended them as such. Conversely, EMI, AARON and other AI systems have no intentions to make art or anything else. Therefore, the works they create are not art, although they could be considered as such if a human had made them. Instead, it’s the software itself that is the art, and its programmers the artists.
With this reasoning, even if we were to concede that the computer-generated works are, in fact, works of art, we can also infer that they are ultimately authored not by computer, but by human computer programmers. In truth, the computer is not the artist, but a tool for making art. A 2010 Pacific Standard article “The Cyborg Composer” quotes EMI’s creator David Cope:
’All the computer is is just an extension of me,’ Cope says. ‘They’re nothing but wonderfully organized shovels. I wouldn’t give credit to the shovel for digging the hole. Would you?’
Indeed, the works created by EMI, AARON and in the Metacreation project are products of the information that their programmers choose to input. “The Cyborg Composer” details Cope’s process:
This program would write music in an odd sort of way. Instead of spitting out a full score, it converses with Cope through the keyboard and mouse. He asks it a musical question, feeding in some compositions or a musical phrase. The program responds with its own musical statement. He says “yes” or “no,” and he’ll send it more information and then look at the output. The program builds what’s called an association network — certain musical statements and relationships between notes are weighted as ‘good,’ others as ‘bad.’ Eventually, the exchange produces a score, either in sections or as one long piece.
Similarly, AARON’s paintings rely on the knowledge that Harold Cohen enters. AARON’s paintings all have similar subjects—mostly people standing with plants. In an interview for PBS’s Scientific American Frontiers, Cohen explains:
AARON can make paintings of anything it knows about, but it actually knows about very little—people, potted plants and trees, simple objects like boxes and tables, decoration. From time to time I wonder whether it wouldn’t be a good idea to tell it about more, different, things, but I can never persuade myself that it would be any better for knowing how to draw a telephone, for example. So I always end up trying to make it draw better, not more.
Therefore, it seems clear that computers will not be replacing or competing with artists, but instead, will continue to evolve as tools that artists can use. But if we see programmer as artist, what happens when someone who is not the programmer interacts with the computer program to make something? For example, George Lewis is a trombonist who has created Voyager, a computer program that plays with a live human player, interacting with that person to create original collaborations. Who should be credited as artist—Lewis, as Voyager’s programmer, or each musician it interacts with, or both? In his essay “Transforming Mirrors,” interactive computer and installation artist David Rokeby writes, “the audience becomes the creator in a medium invented by the artist.” So, advances in artificial intelligence can contribute to the blurring of boundaries between artist and viewer if the viewer also becomes a user.
Additionally, if computers can be used to create works that aesthetically can’t be distinguished from artworks made entirely by the human hand, how does this affect our perception of those art forms? Walter Benjamin’s “The Work of Art in the Mechanical Age of Reproduction” considers the potential effects of the then new-media photography and film on the arts. In the seminal 1936 essay, Benjamin discusses the decline of the autonomous aesthetic experience and the loss of aura, or the sense of detached authority that lies in original, one of a kind works.
The authenticity of a thing is the essence of all that is transmissible from its beginning, ranging from its substantive duration to its testimony to the history it has experienced.
Benjamin suggests a historical loss as a result of technological change. Technical reproduction leads to less emphasis on aesthetics. We can apply this same theory to the computer-generation, rather than reproduction, of art. Artwork that can be created by the computer becomes less special as it becomes less obscure. If we have a tool that can generate a perfect symphony or painting, it becomes less interesting to make these things at all. Accordingly, as computational creativity advances, artists will become less concerned with creating beautiful music or paintings or objects.
This leads us back to Rirkrit Tiravanija and Lee Mingwei, who I mentioned earlier as examples of artists who had created experiences as artwork. Their works are artwork not because they fit into preconceived notions of aesthetics, but in part, because of the intentions of their makers. Indeed, we can create software that generates pleasing musical arrangements or images or objects, but we can’t make a program that will conceive of and intend for particular experiences as artworks. Thus, as the aesthetics become easier to achieve through artificial intelligence, we’ll see a shift in art, with and without the aid of computers, toward the participatory, interactive, socially-engaged and experiential.