How did the closing price rise so high to $432,000? Was it because of the quality of the end product, the quality of the underlying algorithm, the general novelty of algorithmic art—or something else?
In a followup analysis
of the auction, computer science professor Ahmed Elgammal
argued that the rise of AI-generated art as a practice is actually not a novelty at all, but rather is a natural extension of the decades-old art movement of Conceptualism, which values planning and production processes as equally as, if not more highly than, the end result
. “The art is not just in the outcome,” writes Elgammal, but also “in the process that leads to that, including the curated [training] dataset, the choice of the algorithm and its parameters, and the post-curation [of finished works].”
We certainly see that emphasis on process over product in nearly all the media’s coverage of the auction to date. In other words, there’s a much greater public emphasis on, and fascination with, the underlying algorithm as the artwork’s defining merit, rather than any surface-level features of the public-facing portrait itself.
19-year-old AI artist Robbie Barrat, who wrote much of the original code
that Obvious borrowed to generate their Belamy portraits, puts it a bit more cynically: “No one in the AI and art sphere really considers them to be artists. They’re more like marketers.”
What happened at Christie’s last week carries valuable lessons and signals for the future of AI-generated music, and in how its engineers, managers, labels, publishers, booking agents, etc. will value, market and profit from this music in the future.
Of course, the visual arts and music businesses are quite different from each other. Fine art still benefits from a sense of Instagrammable spectacle
, exclusivity and scarcity (even if, in the case of algorithmic art, that scarcity is literally
manufactured), which then drives up the value of its core product, namely the artwork.
In contrast, there is a wide perception that streaming and digitization have not only driven down the value of music, but have also inextricably complicated the concept of a song’s “market value” altogether. After all, digital music is increasingly like an information good
: a stream is the new sale, at least on the charts, and affordable (if not free) access has replaced ownership as the primary consumer demand.
Scarcity does still exist in some form in the music business, especially in relation to legacy artist estates and catalogs. The legacy songwriter catalog market is steadily heating up
with multimillion-dollar acquisitions, while rare vinyl records still sell for several thousand dollars
on sites like eBay and Discogs.
But many investors see the benefit of AI-generated music as further fostering a “post-scarcity” economy
—joining other automation technologies (self-driving transportation, robotics, search, marketing) in drastically lowering certain production and process costs, with the music business as its primary petri dish.
For instance, Spotify could use creative AI to slash licensing costs and populate a hypothetically infinite landscape of mood and activity playlists (hello, “fake artists
”). Artists, labels and advertising agencies could use creative AI to reduce costs by expediting
the songwriting and idea-generation process.
The worst-case scenario is that AI becomes sufficiently “independent” creatively such that it can churn out hundreds of songs in a day, register the proper copyrights for those songs and then flood platforms like Spotify and SoundCloud, which would make the online music landscape even noisier and more unnavigable than it already is today. And then the answer to “how much would you pay for an AI-generated song?” would probably be, well, nothing.
However, if we examine the AI-generated music that’s actually gaining significant, consumer-facing traction and market activity today, it’s not about “flooding the market” at all, and fans aren’t buying into AI musicians for any reason to do with “lowering costs” or cheapening production. In fact, just as with the visual art world, entrepreneurs and marketers are trying to use AI musicians as a vehicle to elevate worth and value by gifting those artificial musicians with more human-like personalities, and hence an illusion of brand scarcity (without the backend costs involved).
To explain further, let’s look at some recent developments in commercial AI-generated music and its closest siblings—e.g. CGI social-media personalities, hologram tours—and examine the scope and source of their market value based on publicly-available data: