Last week, I blogged about how the purported inevitability of generative AI gets used to sidestep moral concerns about it. Earlier this morning, I shared a link to a story from The Verge that illustrates that perfectly, and so I wanted to write just a little bit more about it.

First, let’s quote some more from Jacques Ellul, whom I referenced in the last post (and whom I’ve just been referencing a lot in general recently). Right before the passage I quoted in last week’s post—a passage from his 1980 essay The Power of Technique and the Ethics of Non-Power, he had this to say:

NCII enrages me, but I’m skeptical of this as a solution.

Sure this looks bad, but heaven forbid the U.S. lose AI leadership or whatever.

This sort of thing reminds me why I’m so entrenched in my skepticism of generative AI. There’s an uncritical insistence that the world needs AI, that America should be first in AI, and that we’re just going to have to increase energy production instead of ask ourselves if that’s worth the cost. Credit to Trump, I guess, for illustrating just how dangerous all these attitudes are.

How about a sequel to “The Measure of a Man” where some future tech bro (Trek bro?) uses the events of the original episode to argue that his LLM is sentient, and so Picard, Riker, and Data team up to respond “wtf, no.”

I don’t know that “inevitable” is the right word to use in the title of this post. What I’m trying to evoke is that specific argument about generative AI that now that it’s here, there’s no going back, so the only real/responsible/whatever choice is to learn to use it properly, teach others to use it, accept it as part of life, etc. These are the arguments that the world is forever changed and that there’s no going back—that the genie is out of the bottle so we might as well harness it.

I was already planning to voice skepticism about Apple partnerships with universities in a manuscript I’m writing, but now I’ve got this to cite as well.

Well, if he’s going to ruin the economy, at least he can come by his strategy in the dumbest possible way.

I didn’t need to read a printer recommendation article today, but I’m so glad I did. The rage about the world we live in is great.

Studio Ghibli pictures are neat (legitimately! it’s one of the first generative AI things that’s tempted me!), but these deepfakes are the price we pay for them, and I think that’s too high a price.

I think this is a good example of why digital labor is a particularly salient critique of generative AI. Yes, Wikimedia content is licensed, but not as strictly as copyrighted works. Yet, ripping off of their work is arguably worse than grabbing some copyrighted works.

We keep talking about generative AI as though it’s a tool that can be used for good or bad when I think it’s better to think of it as an entire system that benefits some at the expense of others. It’s not that I want to put a tool back in a box—it’s that I want to live in a better world.

I skipped over this article the first few times I saw it, but I think there’s some good stuff in here. Is defying Ghibli the point?

Generative AI products make me mad, I don’t like them, and I’m not going to defend them. That said, if this gets framed as a copyright problem, is there any way to give Studio Ghibli (or Pixar or the Seuss estate) power to cry foul here that doesn’t also shut down fan art, parodies, and the like? I’m skeptical, and that’s why I think “labor” is the more productive—if more legally ambiguous—framing here.

Really wishing Jesus had told a converse version of the parable of the laborers in the vineyard that I could use for theological arguments against generative AI. You know: Bunch of volunteers make a beautiful community garden that a rich dude takes over to further his wealth.

Look, I don’t have experience running an academic publishing company, but I don’t know if I’d activate the experimental AI summarizer on an article exploring the ethics of generative AI.

Thanks to this article from The Atlantic that I saw on Bluesky, I’ve been able to confirm something that I’ve long assumed to be the case: that my creative and scholarly work is being used to train generative AI tools. More specifically, I used the searchable database embedded in the article to search for myself and find that at least eight of my articles (plus two corrections) are available in the LibGen pirate library—which means that they were almost certainly used by Meta to train their Llama LLM.

This is a mess of a post blending thoughts on tech policy with religious ideas and lacking the kind of obvious throughline or structure that I’d like it to have. It’s also been in my head for a couple of weeks, and it’s time to release it into the world rather than wait for it to be something better. So, here it is:

I am frustrated with generative AI technology for many reasons, but one of the things at the top of that list is the knowledge that today’s kids are growing up in a world where it is possible—even likely—that their middle and high school experiences are going to involve someone using generative AI tools to produce deepfake nudes (or other non-consensual intimate imagery—NCII) of them. See, for example, this horrifying story from the New York Times last April.

The “brute force” metaphor is helpful here, and the article also draws attention to the vulnerability of algorithmic media to generative AI brute forcing.

I believe that scraping the internet to profit off of generative AI is ethically problematic BUT I concede that it should be fair use BUT this is still a soulless and terrible argument.

Oh, please no. I get (and support) that Community of Christ wants to explore doing digital church, but it also has really compelling theological reasons to not deploy generative AI products, and this makes me sad.

Dentist’s office tried to get me to sign away my health data for AI training, but at least I got to talk Astérix with the German dentist and hygienist.

I get a lot of reading done through hoopla, but this kind of story is starting to sour me on the platform.

Throughout my career, I’ve been a data-first researcher, and theory has always been one of my weak areas. This is not to say that I dismiss the importance of theory: I appreciate danah boyd and Kate Crawford’s critique of Chris Anderson’s “the numbers speak for themselves” in their 2012 paper Critical Questions for Big Data as much as I appreciate Catherine D’Ignazio and Lauren Klein’s similar critique in their book Data Feminism. It’s just that while I agree that theory is important, I’ve never been well-versed in it—except for the loose theoretical framework of sociocultural learning, multiple literacies, and social communities and spaces that I bring to much of my work (even that work that has gone beyond educational technology research.

Yeah, it’s really hard to have any sympathy here at all.