Famously vengeful Knicks owner Jim Dolan has long spied on people at his iconic arenas. WIRED goes deep inside the operation that allegedly
reading an article about the guy who owns the Knicks and Madison Square Garden and they used facial recognition to track every move of a trans Knicks fan to try to make sure she didn't end up on game broadcasts and eventually just banned her from the arena.
im posting this here despite the website being extremely white centered, I want people to understand how in this country it's basically ok to murder and victimize black people, especially women and children in the name of "self defense" and white America will reward you for your antiblackness.
trans people don't need to hear your justifications for still enjoying harry potter in 2026 stop looking for forgiveness where you're not going to get it
if i walk into your house and see harry potter stuff, i'm just gonna assume you're a transphobe. no amount of "i got it from a charity shop" can save you from the fact that you value those books enough to display them in your home.
you can't just put the work of someone who's currently trying to eradicate trans people on display without being questioned about it, especially if you claim to care about us.
same goes for your social media, if you're willing to keep putting jkr's work on a podium and proudly talking about it, then it's simply logical to believe that you don't care about other people. it's selfish if i'm being honest, to think that your comfort matters more than the lives of millions.
and to the trans people saying that they're "reclaiming harry potter for the trans community"
no you're not, you can't do that while jkr and her neo nazi friends are currently trying to kill you. you need to let go or else your own community won't be happy to help you when our collective rights are stripped further away.
trans children in the uk are killing themselves because of the things jkr has done.
children are dead. children who should be happy and free to be themselves are fucking dead because jkr has used her immense wealth and social power to change laws specifically to harm trans people. if you really think that your fucking "comfort characters" are more important than the lives of children then you should say that with your full chest. go on. tell the entire world that you don't give a fuck about dead kids. that you don't have an ounce of empathy in your disgusting shrivelled heart, because you still have your shitty fucking books and your garbage movies. your comfort matters more than anything, doesn't it? maybe jkr will tell you you're one of the good ones, wouldn't that be nice?
Like that story isn’t about an ugly duckling that grew up sexy, it’s a fucking swan was judged as a duck and hated itself as a duck until it found out it wasn’t a duck and stopped trying to be a duck.
The actual ducks in the neighborhood were probably still looking around at perfectly normal swans like “damn, look at those busted ass ducks”
although a lot of adaptations skip over this and sanitise it to the point where the message is apparently meant to read "you'll be forgiven for being born wrong, if you turn out thin and white and pretty!" - there's a lot going on in the original. For one thing, most adaptations present him as a wild animal, but the Ugly Duckling is born into captivity, into a society that mimics upper-class pretensions, which is why he's declared 'ugly'. His mother is loving and very generous at first - hatching him despite the inconvenient incubation period, and defending him firmly - but after the other domestic animals (including a higher-class dominant one) point out what a burden he is, she turns on her child. Previously, she genuinely appeared to like him.
And a thing that's missed, while kid's abridged adaptations miss out on the rest of the point, is that the Ugly Duckling decides he can't live like this and leaves the farmyard; he goes into the wild himself. In the various passages in which people try to keep him as a pet, or a duck, it's hammered home again and again that this does not make a good pet. there is nothing in him that suits being a domestic animal.
one of the particular parts that makes you go "sweet jesus, hans christian andersen" is where the wild geese rock up and are nice to the young swan, not quite recognising him as a swan but saying they're pretty into whatever weird vibe he has (is this a sort of queer recognition thing? we are told, explicitly, that the wild geese are both male, and they definitely say "you're so ugly it's hot - come with us" - given HCA, it might be) and then they're, you know, instantly shot dead. Because that's what happens to wild geese. They like your vibe and try to take you with them, and even offer to teach you how to flirt - and then you see exactly what happens to them. And then every encounter from there, from the old woman who attempts to keep him - a very satirical and funny passage - to the young family who genuinely attempt to save his life (but he's too fundamentally panicked and awkward to reciprocate their kindness, and explodes out of their house in a social catastrophe) the story hammers in: not only are you a terrible duck, but you just aren't MEANT to live with people. You're closer to the things they kill than the things they keep.
but yeah, adaptations miss this often: you have to go out into the wild to save your own life. you may die in the wild, and you WILL die where you are. nobody comes to save you - and nobody really could have, when you were younger - but ultimately, mate, you just aren't a very good pet. Of the list of "attributes of a domestic animal" you really suck, in detail, at all of them.
so it's very telling to me that the good ending is the one where he is a wild animal - but more importantly, a WILD SWAN.
Not killed. (like a wild goose).
Not kept. (like a duck).
but a secret third thing, that swans - of few creatures - get. they get admired and they get paid and they get LEFT ALONE. they have a position in relation to humanity, and it is BEING A LOVELY SWAN OVER THERE.
I saw some notes saying "oh wow I need to look up the original." It's very easy! It's here: The Ugly Duckling, by Hans Christian Andersen on Project Gutenberg. It is 3500 words or so and free.
The Ugly Duckling isn't a "fairy tale" or a fable. It didn't emerge from the collective unconscious - it didn't come from nowhere. It's an original work. Andersen wrote it in 1843. It didn't exist before he came up with it. the translation I linked above was translated in 1930.
like many HCA stories (The Little Mermaid, The Snow Queen) it's out of copyright and has pretty images, so it gets mined frequently as a free text - you can always republish a cheap Ugly Duckling, and don't have to pay an author. So people tend to just read and remember the various abridged versions. as a result, they think about it like a fairy tale - a sort of ambiguous, detached, floating thing that belongs to everyone and can mean everything. fairy tales - loose cultural fragments - can be hammered to suit any moral, or handwaved to be about anything, and then when you get bored of them, you can "twist" them a different way. Maybe it's about this. maybe it's about that. I read it as being about beauty. I read it as being about me. I don't like the politics. Today King Arthur is going to be Roman. Tomorrow Sleeping Beauty will wake up by herself. it doesn't really matter. And that's grand! that's what fairy tales have become - they are the people's mental property - they're to be played with.
But The Ugly Duckling isn't a fairy tale. it's a single sad, weird queer guy from a while ago, trying to tell you something personal about himself. maybe he isn't communicating clearly, maybe he's too weird, maybe you don't like it, maybe it annoys you - but <TheUglyDuckling> DOES have meaning and intention.
"I think the moral is this / I think the moral is that" - do try reading it first though! do try reading the whole thing first.
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.
Reblogging again now that Russell Brand's ugly mug is back in the news to remind everyone that in the 2023 Times expose on his abusive behaviour, Daniel Sloss was the only male comedian willing to be named and quoted like "yeah that dude's a scumbag and women have been warning each other about him for years."
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