I had never heard of this character before, but it really was published over a hundred years ago. Here’s a comics blog talking about her, and a couple more gems:
It's hard to believe that this blog has been running over a dozen years now, and I am just now getting around to mak
broooo did you seriously disturb my eternal rest & bring me back to this mortal coil just because my ancient enemy the eternal night has returned? after i sealed it away and everything? which one of you tampered with my binding runes 🙄
where's my useless apprentice i TOLD him it was going to be the duty of the next generation to not repeat the mistakes of those before them and to make this world bet- oh my apprentice goes by her now? you're telling me she's right in front of me! my dear i'm so sorry i didn't know. you look so much more happier and more confident than the bumbling, shy apprentice i once knew. im so proud of you. were you the one who tampered with my fucking runes
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.
There’s an emotion only unlocked when you live in a house with multiple stories. I call it “the stair emotion” and it’s when you realize the object you need is on the other side of yet another trip up and down those goddamn stairs. It’s the closest I get to transcending the desire for material goods. Maybe I don’t need that notebook. Maybe I don’t need anything.
white fantasy authors: okay so white people are from normalsberg and all nonwhite people are from the mysterious mystical kingdom of mystery world where the sands are mystical and weird. and also theyre ugly ass orcs
fantasy readers: this is fucking awesome. this rocks. youre so good at this man
nonwhite fantasy authors: so the knight is a black woman, and there are no orcs,
fantasy readers: okay what the fuck. can we stop bringing contemporary politics into everything. ugh. this sucks. i dont like this
dumbest people i ever met were two protesters outside a show by christian comedian tim hawkins. they were upset by tim's song about wearing his wife's yoga pants. i don't think the bible is that strict about yoga pants
Hey y’all I have an announcement! My web app that I’ve been working on, Afro Index, is now live! It’s a visual reference library of Black hairstyles, for artist, animators, writers, and anyone who wants to learn more about them!
Check it out at afroindex.org! 💛✨
A reference library for Black hairstyles with accurate naming,
structured filtering, and curated reference images.
Following reports that a 20-year-old man had been arrested for throwing a Moltov cocktail at Sam Altman’s home, the suspect stated Monday that he only initiated the attack because he was following a ChatGPT recipe for risotto. “I’ve been using ChatGPT to help with cooking for a while now, so I didn’t think too much of it when the ingredients list included a bottle filled with gasoline and a cloth wick,” said the alleged attacker, who added that he naturally assumed making the rice dish involved driving several hours to the OpenAI CEO’s residence, especially after the AI chatbot had given him a “pretty decent” sesame chicken recipe the week before.
I wish depression were an emergency. I wish someone could take one look at how sick I am and go “oh my god, we need to get you to a hospital!” and then when we get there I get rushed into surgery and the surgeons say “it’s a good thing you brought her here when you did, this is a seriously advanced case” and then they put me under and spend the next ten hours pulling metres of long, sticky black strands of gunk out of my body, throwing it immediately into an incinerator so that it can’t infect anyone else. And then they could stitch me back up and I could rest a few days, and when I leave the hospital everyone can see how much better I am and they congratulate me saying “well done, you’ve been so brave, I’m so glad you’re ok. I love you.”
The kingly pig looks taken aback by this statement. "You claim to be 'baiting' our kind?.. A master of it, no less - after all the trust we hsve placed in you?"
- Your relationship with the Hog Society 🐖 is now Unfavourable.
gummygunk
origamiaround
dailybridgerton
2087
izzy806
kianamaiart
snowghoul
amandla
