AI art is a remix, and we are experiencing an epistemological crisis about it because we don’t have a culturally sanctioned status for the remix as art.

Digital and electronic cultures, dance music standing out as the primary example, have for decades understood art in more layered fashion than the current mainstream paradigm. 

In the underground cultures of dance music, originals can be repurposed endlessly as ”building blocks” for new layers of art, in the form of the remix and the art of the DJ.

These cultures do not reject the idea that a remix or a DJ has a purpose of it’s own, or claim that only the originals matter like some mainstream art critics or record industry strongmen have recently stated. The performance: the order, the emphasis, the presentation, is what matters. The story told by the remix artist with the originals has purpose, if it speaks to the listener’s sensibilities. Bad remixes don’t excite anyone, these are called ”train wrecks” for a reason.

The skill and the art of the DJ as an artist in their own right however, has not been properly acknowledged by the mainstream art paradigm. Even if the reality on the ground is that most art we consume is indeed a remix of some kind, the concept of ”original” has to be shoehorned on everything nevertheless. You are either a copy or an original, there is no in-between.

Enter AI art tools, and a nascent moral panic surrounding them: Effectively the machine learning tools do nothing dissimilar to what the DJ or remix artist were already doing. They allow the user to become a ”DJ of pictures”, to tell a new story by using existing pieces of art as tools.

The moral panic is largely an epistemological crisis: We don’t have a socially acceptable status for the legibility of the remix as art in it’s own right. Instead of properly appreciating the remix and the art of the DJ, the remix, or the meme cultures, we have shoehorned all the cultural properties associated onto an 1800’s sheet music publishing -based model of artistic credibility. The fit was never really good, but no-one really cared because the scenes were small, underground and their breaking the rules was largely out-of-sight. In the case of Hip-Hop music, the issues of licensing beats were pushed into the background, while the rapper took the mantelpiece of ”the original artist”. Controversies with sampling were discussed as anomalies, from which culture largely rubber-banded back into the old model.

However, the future is not bleak: The remix, the DJ-as-artist, bootlegging and other relevant cultural phenomenons were widely theorised in journalism and socio-/musicological academia of the 1990’s and early 2000’s.

As the AI art tools enable the masses to become in the pictorial and written arts as what DJ’s did to the music world, we should look in to the writing some distinguished scholars first before rushing in head-long to paint a picture of what’s happening in the terms defined by whatever the current media zeitgeist supposes us is important.

Recommended reading:

1. Graham St. John
2. Erik Davis
3. Anthony D’Andrea
4. Simon Reynolds
5. Bill Brewster & Frank Broughton
6. Kai Fikentscher

I concur that the AI art tools are simply resurfacing an old problem we left behind unresolved during the 1980’s to early 2000’s. Now it’s time for us to blow the dust off these old books and apply what was learned to the situation we have at our hands now.

We should not forget the modern electronic dance music industry has already developed models that promote new artists via remixes of their work from more established artists. These real-world examples combined with the theoretical frameworks above should help us to explore a refreshed model of artistic credibility, where value is assigned to both the original artists and the authors of remixers, who use their originals to tell a new story, fitting the particular life-story of the particular viewer. Like a deejay spins just the tracks you needed to hear at that particular night of your life at that particularly important moment, the value of the experience encapsulates both the original artform and it’s application to the particular context.

To fully appreciate and integrate AI art in our culture, we cannot rely only on our established models of artistry and credibility. From what was once only a fringe endeavor of collague or plunderphonics artists, mass production tools have forged a mainstream phenomenon. This is however, not our first contact with art like this, and we do have the theoretical frameworks available to form a new class of art, if we reach just a little further into the long corridors of university libraries and the humanities departments for them.

For a more technical & legislative approach to the issue, please see my previous blog post: https://gimulnaut.wordpress.com/2023/01/13/copyright-wars-pt-2-ai-vs-the-public/