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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 is a stripper pole in my attic. i saw it in a dumpster one day, and i went, shit, this is exactly the kind of thing my wife would want. and i didnt really want it in the house, what with it being a used stripper pole lightly seasoned with dumpster juice, but i mentally decided that if she were to see it and ask for it, i would say she could have it, and then sure enough, later that evening, she went soooo baaaaaaaabs there's this thing by the dumpster and i want it but i get it if you don't want it in the house but i have to show it to you- and i went, no you dont, you can have the pole, and that was the most surprised i have ever made her look. even compared to the day when i proposed to her, which she was prepared enough that we both knew she would say yes, and she could also get her hair done up and have a cute outfit, but not so prepared that she was not fucking flabbergasted by the 12 empty decoy ringboxes i sprung on her. i handed her so many decoy ring boxes that day. still one of the funniest things i've ever done to her.
anyway we like pacing around together and ranting in the attic but sometimes instead of pacing one of us will just hang on the pole and spin, and the other person will watch on the beanbag, which makes for these really goofy conversations where the person on the bag will say something that gets the other persons goat, such as, hypothetically, that xylophones do not belong in rock music, and then the other person will go on a tirade about this, but they'll actually only be facing the Hot Take Speaker half of the time, what because of the pole, so the response will sound something like
I can't believe
you would even suggest such
a stupid opinion. You've
been to a Danny Elfman
concert! How can you
have heard Oingo Boingo
live and say with a straight face
that they alone do not justify
rock and roll xylophones
and then that person will continue until they get too dizzy, then they'll get off the pole, and by unspoken agreement, the person on the bag will get up and trade places with them to deliver their rebuttal while also spinning and it just creates this sort of crazy strip-court lawyers debating absolute nonsense for no reason kind of vibe that frankly just really does it for us.
i don't really have any marriage advice for this i guess its just a look at what being married can look like. i thought that being married would involve a lot more stuff like carving the turkey, or barbecuing, or watching the sunset, and if id known how much time it would involve arguing for xylphones in rock music while spinning upside down i might have prepared for it a little differently.
God sometimes I'm writing smut and I'll like, delete a sentence because I'm like, no, I can't write that. It's too indulgent. And then it's like. Girl, what the fuck are you even going to the candy store for if you're just going to buy raisins. Get real.
crazy how the chappell roan security guard thing did turn out to be a huge misunderstanding that ppl used to tarnish a woman’s character after she did nothing wrong. im shocked, that’s never happened before and surely will never happen again right
hrt and transgender surgeries being positioned as dangerous and experimental despite being around for much longer than ozempic, which many people are pushing as a miracle weight loss drug while ignoring its real medical indications and any possible negative side effects
it seems like hypocrisy but it's really the same idea: your body is not yours to control. you are not allowed to be fat, you are not allowed to be trans, we will say whatever it takes to keep you in line
the concept of zosan being around for so long you can collect VINTAGE zosan doujins from the late 90's-early 2000's. and we're STILL getting new zosan content in 2026. thank you opla you are feeding us well
When people argue that food from Chinese and Mexican restaurants in the US are not 'real' representations of that culture's cuisine ignore the historical reality that these dishes were developed by diasporic communities striving to recreate the flavors of home with available resources. Such criticism frames adaptation as a loss of authenticity, rather than recognizing it as a sincere and evolving expression of culture by people separated from their homeland.
now can we perhaps get a major publication to pick up the story of how tumblr's staff is massively hostile to trans women and actively lets harassment directly in violation of its tos proliferate constantly . maybe then our good friend matthew would do something productive about that too
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izzy806
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romaincrisis
tangentwithtanner
