this was gonna be an art blog but I'm gonna go reblogging shit as well so. if you dont want to see a bunch of stuff you may have already seen block the tag "fullcircle reblog"
i know mumbo's breaking out in a cold sweat somewhere after watching scar make the mumbo mannequin make a joke about his disability 😭😭😭 scar you wild, wild man
it’s not really explicitly shippy but that’s what i was thinking about while i did it lmao so the energy is there
the flat color one i might do more w later idk
but i had a starcicle fic* by @mad-c1oud bookmarked since before the server imploded cause i saw a mutual recommend it and i finally sat down and read it like a week ago and omfg i miss qsmp and id never drawn etoiles before (haven’t drawn many members tbh) and i had to rectify that immediately
*link below the cut :) ⬇️
An Archive of Our Own, a project of the
Organization for Transformative Works
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.
I am beyond pleased to announce that an anonymous donor has pledged to match up to $1,000 worth of donations made to our fundraiser in the next 5 days!
That means every dollar you donate in that time counts TWICE, both for the charity and for progress toward our AMV milestones!
Here's some sneak peeks of the AMV team's work so far - and the more money we raise, the cooler these shots will be! >.^
We give you the tools to engage with your donors and raise more for your charity
Look at that, a fancy button you can click to go right to our fundraiser! Go go go!
Writers, start your engines—it's time to start creating!
This year AUfest is a mini-bang, with writers writing complete works of 5k or more, and artists making art pieces to accompany your work. The signup process is simple—writers show the mods they have a half draft during the writer signup period (June 13 - 17) to be entered into claims, and artists put their names in for short lists of works they're interested in during the artist claim period (June 20-21). Mods make teams, and then teams work together for the final half of the event before we all post together.
Wanting to put Tinarose in an arranged marriage? Come on down. Pomme and Sunny are going on an adventure? Join us. Still not over the Copper King's vigil? You are welcome. You need to put the Nosy Neighbours in space? A fantastic thing to do. You want Infernus to take over the world? Who doesn't. Slimeknight need to experience more horrors and you are just the person to do it? Come sprint with us. Shan urban fantasy draft burning to get down on paper? You know an artist can't wait to illustrate that. Flamefrags mafia au sending you visions? You deserve to make that a reality. Joeleo gladiator heist needs to be written? We agree.
Any MCYT, any AU—come join us! Let's head towards our mid-point signups together!
And for writers, one more thing—you have the opportunity to be paired with a beta reader! This is entirely optional, but if you want to be paired up with one of our volunteers, you can submit your information in the form here before midnight EST on the 14th, and there will be a claim process for volunteers to join your team! Feel free to throw your AU into the ring if you'd like, we'd love to have you!
it’s not really explicitly shippy but that’s what i was thinking about while i did it lmao so the energy is there
the flat color one i might do more w later idk
but i had a starcicle fic* by @mad-c1oud bookmarked since before the server imploded cause i saw a mutual recommend it and i finally sat down and read it like a week ago and omfg i miss qsmp and id never drawn etoiles before (haven’t drawn many members tbh) and i had to rectify that immediately
*link below the cut :) ⬇️
An Archive of Our Own, a project of the
Organization for Transformative Works
snowghoul
theartofmadeline
kianamaiart
stormborns
dededos
tangentwithtanner
dailybridgerton
