I have pretty strong feelings against the use of AI around military operations, based on my hands-on experience with the tools. When the tech’s creators say the tech isn’t ripe for warfare, that’s strong feedback. And I agree, with the risks and implications around trust, marketing and hallucinations, it’s not even really ripe for the consumer marketplace, much less drone warfare. Whether or not artificial intelligence tech should be used for war is, of course, at the root of Haraway’s thesis, which we like to noodle with around these parts.

You might call this a taste test: Obsessed with the story about the McDonald’s CEO and how his LinkedIn-style videos selling the McD’s franchise have escaped containment, leading to one of the funnier CEO/product marketing dynamics in recent history. Burger King’s CEO swooped in, holding widely-marketed listening sessions with customers and to demonstrate his love for the Whopper in contrast with the deeply weird McD’s videos. Must read: Internet long-hauler Katie Notopoulos on how direct-to-public marketing works when the public is more familiar with the product than the org’s leaders.

My teenager thinks fast food is cool and subversive (cue the sound of one hundred moms groaning) and she and her friends regularly talk shop. They are Taco Bell fans and think burger stops are kind of gauche. Not gauche: Baja Blast.

In the meantime, the fast food sector is becoming a playground for AI approaches, causing a lot of nervous discussion on social media and in tech spaces.

New blog alert on gender, feminism and gaming: Mothership.

Following the news on Meta glasses this week and how real people are moderating that content loop, watching and moderating all of our intimate video footage, including our most private moments. Last year, my book club read a speculative fiction novel about this very dynamic called “Moderation” by Elaine Castillo. Recommended.

Ryan Broderick is currently my fav reporter on the Internet culture beat, and on this podcast he’s talking about Epstein and why he was interested in putting his resources to developing the early internet (spoiler: for crimes).

Ruling: AI art is not copyrightable.

Apparently one thing LLMs excel at is deanonymization at scale. The original promise of pseudonymity online was social and normative, over and above any question of technical depth: decent people don’t try to unmask you, because why. What strikes me today is how what used to be unacceptably antisocial behavior online is now both automated and unremarkable.

Over the last couple of weeks, I asked a couple of chatbots what could be known about me from this pseudonymous site, where I am more intentional about what I choose to reveal and conceal. It pulled the obvious but also drew conclusions based on a few geographic points I’d made in context that were both revealing and correct. I also noticed that it only drew from the top two pages of information - anything beyond page two of posts wasn’t part of the compute. Archives are for humans?

People assume that there is some computer magic on the backend where the LLMs connect all your account logins behind the scenes, but no, in fact it does all this through inference, by linking your digital trail, your friends, your breadcrumbs of likes and hearts and follows, and obvs your posts, into a picture of who you are, practically and demographically.

Developing a new pet theory that you could theoretically crank AI outputs toward your vision by having an organized link blog revolution.

The Guardian has a long-running series where readers answer one another’s questions, which gives a pretty good point-in-time survey of how people of a certain demographic are feeling on a given subject. This week’s question is on AI futures: “what would happen to the world if computer said yes?”

Reading about a new “slow” RSS app called Current.

Some analysis on Anthropic and the Pentagon. Per @manton, it feels a little bit like the company isn’t fully on board with the product they produce. I find it interesting that the feds appear to be toying with the idea of nationalizing AI companies alongside other nationalization efforts.

A pal sent along this exceedingly cool article on an art space on the south side of Madison, WI, that marries quilting and memory care.

Like Rickrolling on steroids: I didn’t even know P2P music file downloads were still a thing, but of course, and the scene had a big week recently when somebody trolled SoulSeek by generating a bunch of popular songs sung in Homer Simpson’s voice, then quietly polluted the platform by offering the AI generated Homer files up to other users. Someone then set up a digital radio station of all the Homer Simpson songs called D’oh Radio. Here’s more reporting from Gizmodo.

There is a long tradition of Simpsonifying things that go online, so this is the latest iteration. We observed Homer covers going viral on social in 2024 and 2025.

A new report shows that “just 100 users were responsible for almost 70 per cent of online conspiracy posts from influential accounts they examined in Canada.” Relatedly, a White House staffer is reportedly behind a massive Trump account on Twitter. This practice is a common information strategy by bad actors called astroturfing.

A guy put his life savings up against DOGE and won big on the new, anarchic betting markets online. This line hooked me: “Crucially, he’s been around long enough to see promises collide into reality and to know basic federal-budget math.”

Second wavers in tech and engineering talked a lot about the “god trick” of presenting knowledge and information, particularly around math and science, in a way that suggests its objectivity is eternal, immortal, unknowable. Work by Safiya Umoja Noble and others extended this lens to Internet search and architecture, finding that the search algorithm was never neutral, instead it was a series of business decisions wearing neutrality like a costume, creating a customer service experience. LLMs take that same trick and compress it further.

It’s an old idea, and one I’ve been drawing from while I tinker with Claude, which is purportedly the best in the game. The “god trick” is baked right into the AI interface: one input, one output, an authoritative-seeming answer, offered without named perspectives behind it, trained on text produced overwhelmingly by a narrow demographic who has historically had access to both literacy and publishing, by programmers and new media drawing from the same well. Smushed together, it gives the impression that consensus exists where there are in fact many, many loose ends.

I increasingly find it annoying that even “good” AI outputs seem fixed on phrases like “key,” “core,” “exist,” “actually,” “never,” and possibly the worst sentence structure of all time, “it’s not X, it’s Y” — and I’ve begun to recognize how LLMs work like autocorrect for phrases and ideas, drawing from ranked search sources first before fanning out to more obscure sources, trying to determine and assert what’s important to me, a user known by demographics and data. It feels like a big linguistics machine, which is pretty cool in some regards, but also aggressively semantic. The math doesn’t always work to connect me to what I want to find because I am situated in my individual context in ways LLMs are not able to understand, with my memory, in my body, with my unique experiences, which shape and translate meaning for me as I interact with the world (and the web).

And so for you, in your body and memory and experience. An LLM can approximate the outputs of an experience without having access to the experience itself. Sometimes this is useful, sometimes it’s reckless.

Overall the dynamic reminds me of the famous scene from Good Will Hunting: Claude is a smart kid, and he’s never been outta Boston.

An open letter from employees of Google and OpenAI in support of Anthropic, against the DoD: notdivided.org

Looking at this new book by Michael Berube (mensch and legend) on what science fiction can tell us about our contemporary crises. Berube and I used to play Words With Friends together and I assure you he’s a killer.

Where are the women? A brief history of women in the computer sciences.

McKenzie Wark for Verso Books on Donna Haraway, in 2015: “Creating any kind of knowledge and power in and against something as pervasive and effective as the world built by postwar techno-science is a difficult task. It may seem easier simply to vacate the field, to try to turn back the clock, or appeal to something outside of it. But this would be to remain stuck in the stage of romantic refusal. Just as Marx fused the romantic fiction that another world was possible with a resolve to understand from the inside the powers of capital itself, so too Haraway begins what can only be a collaborative project for a new international. One not just of laboring men, but of all the stuttering cyborgs stuck in reified relations not of their making.”