Roundtable
(Non-)Human Explorations into Algorithmic Creativity
Speakers:
Celine Garcia, Nao Tokui, Noah Pred, Sarah Ciston
Profile:
Nao Tokui
Nao Tokui is an artist, DJ, and researcher, and the founder of Qosmo, an AI creative studio based in Japan. While pursuing his Ph.D. at The University of Tokyo, he released his first album and other singles, including a 12-inch with Nujabes, the legendary Japanese hip-hop producer. Since then, he has been exploring the potential expansion of human creativity through AI.
Soundbite:
“I’m not interested in imitating what’s already been created. Nor am I interested in streamlining production to make hit music more economically. AI is a tool that helps you make interesting, meaningful mistakes.”
Nao Tokui, setting out some ground rules for the session
Takeaway:
Part of artists’ responsibility is to misuse tools. Designers never anticipate what creatives will do with their inventions, and the tensions between designers and users pushes tools (and practices) forward. AI intervenes in this process, creating new opportunities for us to be surprised by art, and also necessitating new criteria for evaluating it.
Takeaway:
Like the lawsuits over sampling that happened in the early 1990s, computer-assisted creativity will soon be the site of serious litigation. Many questions of copyright, influence, and derivative works will inevitably soon be in the spotlight, as we re-draw the boundaries between protecting intellectual property while making space for algorithmic (co-)creation.
Takeaway:
Generative approaches to making art are liberatory. They free creators from centuries old rigid framings of where authorship begins and ends, while also creating some space between intent and execution—separating the artist’s ego from the work.
Soundite:
“If a tool is too well-packaged, it’s difficult to misuse.”
Nao Tokui, on keeping tools a little messy and dangerous
Profile:
Celine Garcia
Celine Garcia is a manager and publisher who has produced numerous innovative musical projects. She is the project manager of French musician SKYGGE, who is at the vanguard of AI technologies and music creation. In 2017, she oversaw the publication of SKYGGE’s album, Hello World; shortly after, she joined together to found Puppet Master Label & Publishing in 2018.
Soundbite:
“There are two types of AI outputs. The spontaneous—generated by AI—and the assisted, where the machine or system helps the musician.”
Celine Garcia, clarifying the (quite) different types of art we can make with machines
Profile:
Noah Pred
Noah Pred is a Canadian artist exploring generative audio-visual and multimedia installation work. A Juno-nominated producer, he has released on labels such as Cynosure, Highgrade, and Trapez LTD. Founder of the acclaimed Thoughtless imprint, Pred is an accomplished DJ who has toured worldwide. As a freelance sound designer, he has worked for Native Instruments and Ableton, among others.
Soundbite:
“For me everything ranging from the tiling patterns of ancient mosques to the cut-up poetry of artists like William S. Burroughs falls under the umbrella of generative art”
Noah Pred, pointing out that there has always been ‘automation’
Soundbite:
“Algorithmic tools give us the ability to create compositions with intricacy that even the most talented performers would struggle to perform.”
Noah Pred, on how digital audio workstation (DAW) software and algorithmic tools render traditional notions of musical virtuosity obsolete
Reference:
The third edition of MUTEK AI Art Lab took place in spring 2020 and set out to “explore AI conceptual perspective, to deconstruct popular assumptions about AI, and to investigate our relationship with this cognitive science and its ever-increasing place in our daily lives.” Led by curator Natalia Fuchs, along with organizers Maurice Jones, Peter Kirn, Max Frenzel, and Habib Hajimolahoseini, the team convened a working group of 14 artists from 6 countries including Alexandre Burton, Lucas LaRochelle, and Isabella Salas. “The character of this AI Lab is all about how to figure out where creativity and AI expertise can connect and what they might do together,” explains Kirn in the recap video on MUTEK’s website.
Profile:
Sarah Ciston
Sarah Ciston is a Mellon Fellow and PhD Candidate in Media Arts and Practice at the University of Southern California and a Virtual Fellow at the Humboldt Institute for Internet and Society in Berlin. Their research investigates how to bring intersectionality to artificial intelligence by employing queer, anti-racist, anti-ableist, and feminist theories, ethics, and tactics. They also lead Creative Code Collective—a student community for co-learning programming using approachable, interdisciplinary strategies.
Soundbite:
“AI does not really understand the problem you want to solve.”
Sarah Ciston, quoting Janelle Shane on how our desire to anthropomorphize automation is misguided
Soundbite:
“There might not be machinic agency as such, but generative systems open up new thresholds of speed and scale. Nonhuman generative systems can also offset existing myths of the genius auteur and the omniscient, rational machine.”
Sarah Ciston, moving beyond the usual AI analysis tropes of ‘intention’ and ‘authorship’
Commentary:
Nao Taokui explains that the history of music technology is a history of misuse, misapplication, and misappropriation. The makers of the vinyl record had no way of anticipating turntablism, for example—that was an innovation brought by artists using records “wrong.” Another good example is the early history of the synthesizer and the drum machine, technologies initially created to replace live string sections and drummers for the purposes of creating inexpensive demo recordings. Many musicians at the time were seriously opposed to this. The British Musicians’ Union—bless their hearts—tried to ban synthesizers in the ‘80s. Ultimately, however, artists figured out how to use these tools “wrong,” pushing and bending them to create techno, hip-hop, New Wave, post-punk, house, and basically all the interesting music of the 20th century. This seems to happen again and again: technologies arrive that claim to simplify a process while implicitly displacing or automating creative workers, until creative workers stop that from happening by making the technology central to a new form of creative work that only they can do. It’s like defusing a bomb by turning it into an engine. Why should AI be any different?