Modern forms of generative art
Generative art meets crypto art
In the generative art process there are always two roles:
the composer, who designs and implements the code that generates the artworks, and
the curator, who chooses the most interesting outputs from the many generated ones.
We will see how these roles, and in particular the curator’s, can be played by different actors in different forms of generative art.
The text on this page has been previously published in the NFT paper Past, Present and Future Forms of Generative Art by hex6c.
Single-form generative art
These first digital pioneers - like the 3N of computer graphics Georg Nees, Michael Noll, and Frieder Nake - used archaic programming languages like Algol and Fortran. The corresponding code generated punched tapes. When read by a computer these tapes printed an output using some form of drawing machine, like the Zuse Graphomat Z64 used by Georg Nees and Frieder Nake.
Given the inherent limitations of this early creating process, the output was typically a single piece.
In this form of generative art, the composer is the artist (the programmer), while the curator is in fact the machine, since it was responsible for picking a single output from the many possible ones (assuming randomness was used in the code, which was frequently the case).
Short-form generative art
Recently, generative art, as a privileged form of digital art, has experienced a second youth thanks to blockchain technology. Blockchain technology, while commonly associated with cryptocurrencies, has the potential to bring radical structural change to the arts and creative industries.
Crypto art is digital art minted and traded on a blockchain. In crypto art, an artwork is associated with a Non-Fungible Token (NFT) that certifies the scarcity (number of copies), ownership (current owner), and provenance (historical owners and creator) of the work of art. Transferring the NFT on the blockchain is akin to transferring the certificate of ownership of the artwork.
Crypto art draws its origins from conceptual art, sharing the immaterial and distributive nature of artworks, and the rejection of conventional art markets and institutions. A niche artistic movement until early 2020, the crypto art market went parabolic in late 2020 - also because of the COVID pandemic - attracting the attention of major mass media and major auction houses.
In modern day generative art, due to the abundance of computational resources (computing power and memory), a generative artist typically runs the code and generates a large, potentially unbounded number of outputs. Then, the artist picks the best highlights, often a single output, and possibly mint it as an NFT on a crypto art marketplace.
In this generative art form, the artist is both the composer and the curator of the generative art process.
Long-form generative art
Recently, generative art NFT marketplaces like Art Blocks on Ethereum and fxhash on Tezos allow for something different. The artist-programmer does not simply create an artwork, but writes a program, which is stored on-chain and generates a very large number of different outputs.
The algorithm uses a hash (a hexadecimal string encoding a block of information) as a source of randomness and the output is totally determined by the hash. Therefore, different hashes will produce different outputs. The collector chooses one of the available projects, for which there is at least one example of output.
The collector buys an execution of the chosen code at a given price.
The code generates the artwork and the associated NFT is transferred to the collector’s wallet. Neither the artist nor the collector know in advance what the output will be.
Basically, the original idea of this generative art form is to distinguish between the score (the code) and the execution of the score (the output of the code). Generative art thus becomes a performance, just as when we attend a concert knowing the score but ignoring what the musicians’ performance will be like.
As Tyler Hobbs notices:
This form of generative art introduces the new demands of consistent quality and high variety, while maintaining the existing need for unity across all output from a program.
Quality and variety are somewhat opposing forces and it is hard to maintain both for a large number of executions. For this reason, the artist must limit the search space of the outputs of the code, trying to maintain a good average quality among the outputs and avoid outliers.
Similarly to the making of short-form generative art, also in long-form generative art the artist-programmer plays both the roles of composer and curator of the generative art process. However, the curation step is fundamentally different.
While in short-form generative art the artist cherry-picks the best outputs to highlight them, in long-form generative art the artist needs to be very skillful to inject the curation step into the code. In some sense, the code must have the knowledge of where the good outputs are in the search space.
Unbounded-form generative art
There is, however, a hidden pitfall in long-form generative art. In order to encode the curation step inside the code, the algorithm needs to artificially bound the output search space. While this limits the possibility of getting a low-quality result, it also cuts off the chances of generating unexpected high-quality outputs.
Notice that so far the role of the collector was not an active one. In particular, the collector takes no part in the creation process. In single-form and short-form generative art, the collector passively buys what the artist offers. In long-form generative art, the collector mints the artwork, but the actual artwork is chosen by the algorithm.
In unbounded-form generative art the algorithm is free to explore the entire search space of outputs. The collector can generate an unlimited number of outputs and pick one among them for it minting as an NFT.
In unbounded-form generative art, the composer is the artist and the curator is the collector.
QQL is a project of unbounded-form generative art.
Community-form generative art
The last form of generative art, dubbed community-form generative art, leverages collective intelligence.
In this case, the curator is a community of individuals and organize themselves, possibly in the form of a Decentralized Autonomous Organization (DAO), to guide the generative process and choose the future outcomes.
A popular example is Botto, a decentralized autonomous artist. It creates works of art based on collective feedback from the community. The human participation is what completes Botto as an artist.
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