Remember when Lil Nas X beautifully explored his sexuality, seduced and killed the devil to the banger of all time, and instead of cheering on this openly gay and proud Black artist for his artistry and fighting back against respectability politics, suddenly said respectability politics was all the Queerest Place on the Internet cared about? Hm. Wonder what happened there.
Anyway I miss him and hope he's doing better with his mental health 🙏🏾
Like say what you want about "bad queer representation", but this was the song that made me openly and happily accept that I was bisexual. To see him up there Black and beautiful, making music that I love, absolutely killing it? Yeah. You couldn't tell me shit. This man made me proud to be out. "This will make them think we're evil for being gay" hey newsflash dawg-
i think we should be ridiculing them more for this. you don't get to try and go all "queer website" when your staff likes to go on nuking sprees targeting the trans fem users
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.
Do not forget that discord is still planning on moving forward with age verification and has only "delayed it" until "the later half of 2026." They are hoping you will forget while they quietly roll it out when no one is looking. Continue to message them about it. Continue to talk about it. Make it clear this is unacceptable. Discord is one of the only places left you can even talk about or share adult content in private at scale anymore. They will tell you "its not that bad if you dont use it for nsfw" but fuck them and fuck people who say that shit.
CeCe Rogers on Facebook writes: "Two Black Tennessee lawmakers were physically escorted out of chambers this week while Republicans quietly held a hearing to approve gerrymandered maps that would eliminate the state's only majority-Black congressional district.
No referendum. No special election. No public vote.
Because they know what happens when voters actually get a say — just look at Virginia, where the people spoke so loudly that Republicans had to drag the courts in to override them.
This isn't new. During Reconstruction, Black Americans held more congressional seats than at any point in the prior 90 years of American history. And white supremacists spent the next several decades tearing that down, through gerrymandering, poll taxes, and voter intimidation.
150 years later, the same tools. Different suits.
The audacity of escorting Black lawmakers out of their own chambers while dismantling Black political representation, and then telling us the courts aren't political, is breathtaking. These are the same courts they're counting on to make it stick.
This is a coordinated, multi-front assault on Black Americans. And we need to say it exactly that plainly."
i wish everyone following me made enough money to not feel like they were being boiled alive and had the time and energy to clean their room at their own leisure
Please give us your data 🥺🥺🥺🥺 For the children 😢‼️ all of your legal information 🙏🙏 yes 🥺 your home address? 🥺 Your government issued ID 😢❓social security number and credit card details 🤗 immigration status ❓ racial religious and gender identity 😁😢😢😢⁉️ please 🥺 did you get an abortion this year 🥺 please give us your personal information 🥺🥺🥺🥺 for the children‼️‼️
it’s funny how we’re getting to the point in the AI lifespan where you can feel the desperation from tech companies to have you use their AI features. instagram has moved their AI effects to the top of the menu when you’re creating a post for your story, exactly where the draw/edit button used to be. gmail is creating one-click AI-generated replies right before you open up the text box. spotify put a beta AI playlist generator on the front page that looks just like a search bar so all of their users accidentally click on it when they go to search for a song.
tech companies are shaking in their boots trying to prove to shareholders that their investment in AI is worth it, to the point where they’re tricking their users into using the AI features even for a split second in order to fudge the numbers. like awww is your little environment-destroying toy not wielding the results you hoped for? so sad!
I think the context of what you experienced before writing this post is important. Because holy shit, the amount of fatphobia dripping off of what that person said to you is so fucked up
This world is so fatphobic that people would rather be thin with gender dysphoria than even POTENTIALLY have a fatter body while being the gender they identify as. What the absolute fuck is wrong with this world. I'm fucking done. I knew that fatphobia was bad in the queer community as a queer person myself, I knew that this was especially so in trans communities, I even knew that a lot of my fellow trans people lament weight gain due to transition, but I somehow had an ounce of hope not yet pummeled out of me. My mistake! :)
