I reblog political things I care about, as well as memes, and shitposts, and art. And whatever the wlw flamingos are doing I may be nearby. Or at least reblogging queer shit. I talk about writing a fair bit too.
I am not immune to fandom nonsense. I write fic. Current/past fandoms: Severance, Succession, Ted Lasso, Hacks, season 1 Supergirl. Old school X-Files (yeah this one is the loudest right now)
Devil Wears Prada is eternal.
I believe in tagging stuff. But if I've dropped the ball and there's something I reblog/post that you want to be able to blacklist, give me a prod.
1. The court holds Google responsible for statements made by its AI, considering them Google's statements (search engines have limited liability for results in their engine as they're the words of other sites/companies/people), meaning when their AI lies/hallucinates they're liable for the defamation/harm resulting from those statements.
2. Google's defense that customers are generally aware of the lack of reliability and are responsible for fact checking was dismissed. As the court pointed out, that would "significantly diminish" AI Search's stated purpose and it can't be distinguished from Google's business practices/statements as a search tool.
3. Studies have found about 91% of Google's everyday AI responses are accurate, leaving millions of searches per HOUR with potential liability for falsehoods. 56% of correct responses weren't supported by the sources the AI listed. Both of which mean Google is now liable for a LOT more AI "errors."
4. Google was held liable for 80% of court costs in this case and this precedent is expected to reverberate around the world. This is a massive shift from the 3rd-party search provider role Google has previously played and it comes right as they've tied ALL searches to their AI search.
Additional source and more details below. Absolutely thrilled to say that this is real. And yeah, it's huge.
For all the reasons above AND ALSO because this particular lawsuit is a defamation case
Privacy lawsuits are hard because most privacy laws are super super weak, and there's very rarely a lot of money or enforcement backing privacy laws for...twenty million reasons, really...
But defamation suits? Those have teeth.
(In large part because, at least in some countries and including in the US, defamation laws protect public figures the least - and "public figures" legally includes most if not all politicians, and a hell of a lot of other rich ppl too)
A Munich court ruled Google's AI Overviews are its own words, making it liable for false claims, a decision that, if it holds, could reach e
A German court has ruled that Google can be held directly liable for false claims made by its AI Overviews, a decision that could put a serious legal dent in the whole “the AI made me do it” defense.
According to The Next Web, the Regional Court of Munich issued a temporary injunction after Google’s AI Overviews wrongly tied two Munich publishers to scams, subscription traps, and dubious business practices. The court treated those AI-generated summaries as Google’s own statements, not just ordinary search results pointing to third-party pages.
That distinction matters. Search engines have traditionally had more protection because they index and link to other people’s content. AI Overviews changes the machinery. Google is not just showing the web anymore. It is summarizing it, rewriting it, and sometimes apparently hallucinating a tiny legal grenade into the results page.
There's an awful trend in reading that's this CinemaSins kind of rejection of abstract concepts and suspension of disbelief, that makes people say it's bad writing when authors use descriptions that aren't immediately one to one with physical reality.
Like it's bad when a "tattoo is undulating" (as opposed to... "drawn in a wave like pattern on the skin"?), or when hair is "wet wheat from a late Summer field" (as opposed to "sort of brownish light yellow that dries lighter, but is not actual wheat stalks growing on someone's head but kind of reminiscent of the color and texture"?), or when when ice cream tastes like midnight at the fair" (as opposed to "ice cream flavour bringing back memories of undefined ice cream flavours that are individually popular but always tied to a memory of late evening at the fair ground and probably smelling vaguely like popcorn and sugar"?).
Please. We have to get back to understanding abstract descriptions that evoke feelings and memories and mental images or things we haven't experienced yet. This hyper utilitarian way of reading and judging text is killing fiction. it's robbing you of experiencing things you haven't actually personally experienced.
404 has been knocking it out of the park since they started. Please support their original reporting on this! If you subscribe to nothing else I highly recommend them. Their podcast is great too.
Planning documents for "Scout" say the plan is to "make people addicted" to the tool before adding new features.
Text of tweet under the cut because it is loooong.
But... Stochastic Parrots.
Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.
Her name is Timnit Gebru.
She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.
The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.
The paper had not even been published yet.
Here is what she actually wrote, and why every prediction inside it has now come true.
The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.
This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.
The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.
The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.
Every one of those things has now been documented in deployment.
Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.
The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.
In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.
The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.
In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.
The fifth warning was the one Google cared about most.
Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.
This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.
The paper Google fired her for predicted the model collapse problem before model collapse had a name.
The mechanism behind why this all happened is the part of her work that nobody quotes.
Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.
She was making that argument from inside Google.
Then Google proved her right by removing her.
The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.
Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.
Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.
The question worth sitting with is the one almost no one in the industry will say out loud.
Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.
The researcher Google fired for warning about exactly what is now happening was right.
The company that fired her is now the second-largest deployer of the technology she warned about.
And the people inside that company who agree with her are not allowed to say so.
January 1996:
QUESTION: "What do you think Scully's dog should be named?"
GILLIAN: "There were two names that I came up for it. One was
Clyde -- but that's my husband's name, so.... The other was Yappi. [Cheering] Which do you like?"
QUESTION: "I prefer Yappi."
GILLIAN: "You like Yappi? That's the most obvious one, I would have thought."
May 1, 2013:
Q: Gillian Anderson, do you have a dog?
GA: You know, buddy, I don't have a dog. I used to have a dog. Oh, Queequeg! You want to know about Queequeg.
GA: Queequeg died, sweetie.
October 12, 2013:
everdeer: Don't you guys think Queequeg deserved better?
DavidDuchovny_: Yes.
gilliananderson: No. That dog killed people with its farts and it deserved to die a nasty death in the mouth of that alligator or whatever it was. Ugh. I had to shampoo it, or walk away every few seconds, because these puffs of nastiness kept happening.
DavidDuchovny_: "Puffs of Nastiness" should be your band name.
[Bonus: hilarious double standard--
April 1996:
A gunmetal grey trailer home, parked just to the left of the main X-Files set, is Gillian Anderson's sparsely furnished, functional home-from-home. Inside, Cleo, a large, black, slavering hound of undetermined breed is throwing toys from one end of the trailer. And she's farting. "Oh Cleo!" says Gillian. And then to me, "It's the food we're giving her."]
March 22, 2026:
Q: Knowing what you know now, what would you tell your past self?
GA: My past self? [Q: Yes.] My younger self? [Q: Yes.] Or myself in a different life? [Crowd laughs.]
Q: Younger self.
GA: Okay. My past self: don't come back as Queequeg.
idk i just feel like "it is more acceptable and in fact encouraged to mock anything enjoyed primarily by women" and "being enjoyed primarily by women does not make thing feminist and righteous" are thoughts that can and should coexist
shipping isn’t about what the writers or actors say is or isn’t romantic. shipping isn’t even about romance a good percentage of the time. shipping is about seeing The Dynamic and going absolutely hog wild in your mind and your friends dms about it.
You ever think about many peices of media have zero women and thats just perfectly normal but if a peice of media has an all female cast people get... like that? Women should be allowed to kill over this btw
i was speaking with a guy i work with and when leaving i said okay see you monday and he went oh no i wont be in monday. im going bald. and i said ?you're what? and he just repeated im going bald monday. wont be in
Imagine being the gays at a pride event in 2004 living their lives when someone grabs the microphone and announces to the room that Ronald Reagan was pronounced dead. Can you even imagine the hype, the celebration, the pure elation
