Below are posts associated with the “generative AI” tag.
🔗 linkblog: In desperate times, graduates find hope in humiliating tech CEOs
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).
🔗 linkblog: OpenAI Announces Construction Of New Data Center On Top Of Sick Child
I apparently haven’t been watching enough video content from The Onion, because this was a treat.
🔗 linkblog: How Deepfakes Tore a High School Apart
Stories like this should take a prominent place in every discussion about generative AI.
🔗 linkblog: 4chan’s Misogynist ‘Wizards’ Are Nudifying Women by Request
I will (almost) always post articles that make me angry about NCII.
🔗 linkblog: America’s dangerous, messy deepfakes crackdown is here
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?
🔗 linkblog: AI-generated research papers are overwhelming peer review
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.
🔗 linkblog: Meet the Sad Wives of AI
Embarrassed to say that this gender dynamic of AI had never really occurred to me before. Interesting read.
it sure looks like David Kloiber is creeping on University of Kentucky employees to send them personalized mailers for the KY-6 primary
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.
🔗 linkblog: Data center guzzled 30 million gallons of water and nobody noticed for months
Shouldn’t be reading this before bed because it isn’t calming me down.
🔗 linkblog: Your AI Use Is Breaking My Brain
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.
🔗 linkblog: I Work in Hollywood. Everyone Who Used to Make TV Is Now Secretly Training AI
It’s digital labor all the way down. What a depressing read.
🔗 linkblog: Book publishers sue Meta over AI’s ‘word-for-word’ copying
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.
🔗 linkblog: University Professors Disturbed to Find Their Lectures Chopped Up and Turned Into AI Slop
Well, this is certainly… something.
📚 bookblog: Old Media (❤️❤️❤️🖤🖤)
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.
🔗 linkblog: Pluralistic: A Pascal’s Wager for AI Doomers (16 Apr 2026) – Pluralistic: Daily links from Cory Doctorow
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.
🔗 linkblog: Ronan Farrow on Sam Altman’s “unconstrained” relationship with the truth
This was an enlightening listen on my way into work this morning.
hallucination in the LLM-based Kagi Translate
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).
🔗 linkblog: The Deepfake Nudes Crisis in Schools Is Much Worse Than You Thought
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.
🔗 linkblog: To teach in the time of ChatGPT is to know pain
Really appreciate this essay. It puts things nicely and has the kind of personal investment that makes it relatable.
🔗 linkblog: Police corporal created AI porn from driver's license pics
So gross. I don’t think we can talk about generative AI without talking about this.
🔗 linkblog: What the heck is wrong with our AI overlords?
I wrote recently about how my concerns about (generative AI) are probably more about the broader Ellulian system of technique than the specifics of the technology. Here’s a passage from this article that makes a similar point better:
For some tasks, AI really is amazing; the tech behind things like machine-learning algorithms and large language models is ingenious, but the results always seem to be hawked the hardest by people and companies I don’t particularly like or trust. (Heck, Anthropic used one of my books to train its database, a sin for which it is now paying authors in court.) Give me the same sorts of tools but under my local control, governed by a Wikipedia-style nonprofit and trained on ethically sourced data, and I’d use them a lot more.
🔗 linkblog: The New York Times Got Played By A Telehealth Scam And Called It The Future Of AI
Masnick’s fierce critique is all the more notable for how public he is that AI is good for some things, pushing back against grumpier folks (e.g., me).
Check this paragraph out, though:
What we actually have here is a marketing operation that used AI to automate the production of deceptive advertising at a scale and speed that would have been harder to achieve otherwise. Snake oil salesmen have existed forever. What AI gave Matthew Gallagher (and, I guess, his affiliates) was the ability to crank out fake doctors, fabricated testimonials, and deepfaked before-and-after photos faster than any human team could — and to do it cheap enough that a guy with $20,000 and no morals could build it from his house. That’s the actual AI story the Times should have written.
🔗 linkblog: DOGE Goes Nuclear: How Trump Invited Silicon Valley Into America’s Nuclear Power Regulator
So much about this that I don’t like. The article makes a good case that there may be good reasons to ease up on nuclear power regulations, but the language of AI and VCs suggests to me that those good reasons aren’t the top priority.