This is an essay I wrote in 2022, inspired by Kyle Chaka’s 2016 viral essay, “Welcome to Airspace”. After seeing an excerpt from Kyle’s new book on the front of /c/Technology, I thought y’all might be interested in reading this piece of mine, which is less about the design of physical spaces, and more about The Algorithm™'s influence on creative practice in general.

This is a conversation I can have a million times, so I hope you enjoy.

  • theluddite@lemmy.ml
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    6 months ago

    I actually think that this is part of a larger phenomenon. It’s something that Adorno and Horkheimer identified all the way in the 1940s (in “Dialect of Enlightenment,” especially in the chapter “The Culture Industry”) that is now greatly accelerating because of computers. The result is what I call The Tyranny of Data. The essay isn’t that long and most of the length comes from examples, but I’ll try to do a super quick tl;dr of my argument. Here’s some Adorno and Horkheimer quotes that I cite:

    For enlightenment, anything which does not conform to the standard of calculability and utility must be viewed with suspicion.

    and

    Bourgeois society is ruled by equivalence. It makes dissimilar things comparable by reducing them to abstract quantities. For the Enlightenment, anything which cannot be resolved into numbers, and ultimately into one, is illusion[.]

    Basically, modern society culturally values arguments presented in numbers, especially when expressed in units of currency. I argue that now that we have computers, aka a machine capable of turning everything into numbers very easily, we can easily collapse everything into units of currency. This is a homogenizing and conservative (as in change averse) force (quoting myself):

    You can measure how people feel about another Marvel movie, or a politician they already know, or whether they prefer this version or that version of a product. It’s much harder to measure interest in a brand new movie idea, or an unknown politician, or a radically new invention. The bigger the change, the harder it is to measure.

    Because it’s so easy to turn things into numbers now, and because we culturally value data-based arguments as superior to other kinds, like moral or ideological, our collective ability to think in other ways is atrophying. As a result, we struggle to take the necessarily irrational risks that we need to take to make real progress, be it social progress, artistic progress, or whatever.

    I go through a bunch of examples, like Joe Biden, who I call “a statistically generated median in corporeal form. He’s literally a franchise reboot, the single most derivative but fiscally sound cultural product.” I specifically talk about digital media too:

    When deciding how much to value websites or podcasts or any other online media, we simply add up the number of downloads. No one actually thinks that’s a good way to decide the value of art, writing, journalism, story-telling, lascivious true crime blogs, or reality TV rewatch podcasts. It’s just the first number that fell out of a computer. Just like that, a complex social situation was transmuted into a number.

      • theluddite@lemmy.ml
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        6 months ago

        Yes absolutely! Debord comes up a lot on my blog too. I fucking love the Situationists. A lot of these theorists that lived through the earlier days of mass media saw it with such clarity for exactly what it is in a way that those of us born later I think would struggle to see were it not for their writing, not that we bothered to heed their warnings.

    • zbyte64@lemmy.blahaj.zone
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      6 months ago

      And now we accelerate the process with generative AI, resampling data into “new” content for profit. But I can’t shake the feeling this will be an undoing, like it somehow devalues the collated data becauce it becomes so abundant (and synthetic).

        • zbyte64@lemmy.blahaj.zone
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          6 months ago

          Fantastic read, shared at work and now following on mastodon. Also had this thought in regards to my own work:

          … I find it reflects a similar problem we’re having with our code base: “simple is not always easy”. This article points out that Generative AI does what is easy/cheap, when what we really need is simplicity (or simplified complexity)

          There’s probably another article to write about this, I would title it: “Generative AI won’t solve your Cynefin domain problem”

          • theluddite@lemmy.ml
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            6 months ago

            Couldn’t agree more! We shouldn’t outsource planning the world that we want to make to oversimplified heuristics, including “whatever is cheapest.”

      • Snot Flickerman@lemmy.blahaj.zone
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        6 months ago

        That’s well documented already. The near-instant proliferation of AI generated content on the internet means that in short order, AI’s are ingesting data from earlier, more crude implementations of AI. The AI doesn’t know that one source is better than another, so as it scrapes the internet, and the internet becomes more full of AI content, the content produced begins to slowly become useless as more and more AI-generated content becomes the source for the AI to generate content.

        AI is an ouroboros, the snake eating its own tail.