20,000 accounts is a hell of a “bug.”

Don’t love the idea of AI as coparent, but gendered divisions of labor also suck.

“Scale” and efficiency aren’t always good, and digital blackface is a good example.

Digital labor is, imo, the fundamental problem with AI, and I think this story shows why: It’s not just the AI use here that’s exploitative, it’s kind of everything.

Check this guy out:

He compared the current era of AI to the Tower of Babel, saying society must “avoid the ‘Babel syndrome,’” which he defines as “the idolatry of profit that sacrifices the weak, a uniformity that neutralizes differences, and the pretense that a single language — even a digital one — can translate everything, including the mystery of the person, into data and performance.”

I think I like this pope.

Ugh, gross.

The purported inevitability is one of the most frustrating things for me about AI, and I think this shows that I’m very much not alone in that feeling. (Also, mandatory Ellul reference).

I apparently haven’t been watching enough video content from The Onion, because this was a treat.

Stories like this should take a prominent place in every discussion about generative AI.

I will (almost) always post articles that make me angry about NCII.

To echo a comment I made earlier today, I will always hold tech companies morally responsible for the harms they cause, but I get a lot less sure about legal responses. Do we trust this administration to handle NCII properly?

Here’s a gift link. Jacques Ellul argued that you can’t separate the good aspects of technique from the bad. In that context, this paragraph stands out:

Optimists about generative AI have high hopes for its ability to produce future scientific breakthroughs — accelerating discovery, eliminating most types of cancer — but the technology is currently undermining one of the pillars of scientific research, inundating editors and reviewers with an endless stream of papers. Paradoxically, the better the technology gets at producing competent papers, the worse the crisis becomes.

Embarrassed to say that this gender dynamic of AI had never really occurred to me before. Interesting read.

Kentucky primaries for the 2026 elections take place a week from today, so it’s not surprising that we’ve been getting some political mail over the past couple of weeks. Today, though, something came in the mail that really took me aback. David Kloiber’s campaign sent us something that was clearly more than a regular mailer, since it came in a letter-style envelope and was addressed to both me and my spouse.

Shouldn’t be reading this before bed because it isn’t calming me down.

Long before I ever knew what generative AI was, I was grumpy about the idea of Grammarly because I was suspicious of deferring to a computer on what “good writing” looks like. I appreciate Koebler’s thoughts here for the way it shows how generative AI—including Grammarly now, apparently—is doing something similar on an even larger scale.

It’s digital labor all the way down. What a depressing read.

This is a good example of how thorny the AI problem is, and why I strongly prefer a digital labor critique to a copyright critique. Yes, I’m mad that Meta trained their models on my work, but I don’t think the answer is to strengthen Elsevier or Cengage’s copyright claims.

Well, this is certainly… something.

Eh, it felt like this was a continuation of some of my least favorite parts of Autonomous. I am also struggling to enjoy “robots’ rights” stories in our LLM era, which is dumb, but that’s how it is.

I’ve felt for a long time that “what if AI gets sentient and does irreparable harm” is 100% the wrong way of framing things, and Doctorow knocks that argument out of the park here.

This was an enlightening listen on my way into work this morning.

You don’t have to spend long on my blog to figure out that I default to being grumpy about generative AI, but if I’ve made one exception to that rule, it’s for Kagi Translate, which I’ve found to be a genuinely helpful machine translation tool—and to have some neat features that I haven’t found in its Google or DeepL equivalents.

It took me back a little bit tonight, then, when Kagi Translate straight up hallucinated something on me, in a way that I imagine wouldn’t be out of place for a more mainstream LLM (which I’ve never really used). Earlier today, while working on a paper for an upcoming conference, I was consulting a Jacques Ellul book I was about to cite, and I wanted to make sure that “genetic engineering” would be an accurate translation for his phrase « intervention génétique » (which could obviously also be rendered “genetic intervention,” but I’ve never heard that phrase in my life, so I’d prefer to go with a more well-known phrase if it’s accurate).

Audrey Watters once compellingly argued that metal detectors are edtech. I think we now have a responsibility to treat AI nudifier apps as edtech, too.