A lot of this is still unresolved in my mind, but I think there is something interesting happening at the intersection of generative AI, art, style, and entertainment. Rather than letting it gestate until more fully formed, I figured I’d just post some preliminary thoughts and come back to this at some later date.
The main reason I’m thinking about this now is the ongoing debate about how generative AI will impact creative fields, such as writing and design (as well as white collar jobs more broadly). Arguably there have already been some pretty dramatic effects, such as the sci-fi magazine Clarkesworld being suddenly overwhelmed by spammy submissions. At the same time, it’s hard to know the extent to which these disruptions may end up being transient phenomena that broader systems will adapt to.
I recently started listening to the Art of the Score podcast, which does an amazing job of unpacking movie soundtracks in depth, beginning with Raiders of the Lost Ark in the first episode. Like most such explorations of music, however, it ultimately leaves me wanting something that I’ve long thought there should be much more of—namely, more tightly interwoven cultural commentary, especially for music. As I will describe below, I’m broadly interested in different ways of combining context, commentary, and criticism with the thing being commented on or critiqued.
Last week’s speaker in the Penny Stamps Speaker Series was Refik Anadol, one of the most successful artists working primarily with AI, data, and visualization. Over a decade or so, Anadol has produced work in collaboration with organizations and venues like the LA Philharmonic, Gaudi’s Casa Batlló, the Exosphere in Las Vegas, and the Museum of Modern Art in New York.
The lecture he gave was basically a review of his body of work, and that of his art and design studio, which is comprised of about 20 people. The earlier projects he showed mostly took the form of massive scale light projections on the sides of buildings, which could give the impression of a totally different texture or form. More recent work tended to use data driven visualizations, abstracting some sort of data into visual patterns displayed on a wall, building, or screen. Many of these also made use of what appeared to be procedural animations to create the impression of three dimensionality and motion.
There is a duality at the heart of large language models. On the one hand, they are essentially a backwards-looking invention, a “cultural technology”, in the words of Alison Gopnik—algorithms which index and remix a large slice of human culture (though one that is typically heavily biased towards the recent past). On the other hand, they can often seem to be producing something entirely new, and can thereby leave many people with the impression of having a personality or even “sentience” (whatever that means exactly); in the most extreme cases, some people have apparently convinced themselves that such models are a step on the path towards some sort of successor species to humanity, a new regime of algorithmic children that will survive our own human catastrophes. Complicating matters here is the fact that the emergence of and widespread attention to these systems largely overlapped with the Covid-19 pandemic, a time in which we have all had additional reason to reflect on life, death, loss, and creation.
It was recently reported by inews.co.uk that Twitter is going to start charging academic researchers and institution $42,000/month if they want to maintain their current level of expansive access to data, and – more significantly – require that they delete all Twitter data from their archives if they do not. I’d heard rumors that this might be happening a few weeks ago, but the iNews article is the first independent reporting that I’ve seen about it.