every day it just concerns me how little compassion people have. no compassion for those living in the global south. no compassion for immigrants. no compassion for disabled ppl. no compassion for addicts. no compassion for prisoners. no compassion for children. like holy shit ...
i made a separate post about this but actually there are plenty of people cough white people who care about animals more than they ever do human people . not what i'm talking about make your own post
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.
Reminds me of the time we dared a brick oven pizza restaurant to make a pizza with so much garlic we couldn't finish it.
Boy did they deliver. The pizza had (no exaggeration) a solid inch of chopped garlic on top. It was fucking delicious. Multiple times we spotted restaurant workers peeking at us from the kitchen, with an obvious "my god they're actually eating it!" energy.
Of course we left a massive tip. Leaving the place we felt like triumphant Olympians gold-medaling the Pizza Event.
Only one problem.
This was a lunch time experience, and we worked at a small software development firm and there was a scheduled all-hands meeting after lunch. Our supervisor (politely) asked us to leave the meeting because we reeked of garlic.
HOLY SHIT GUYS, I WAS INSPIRED BY THIS POST TO TRY MAKE THE SONG AND YOU WOULD NOT BELIEVE THE SCREAM I SCRUMPT WHEN I DRAGGED THE TRAINING AUDIO OVER THE BACKING TRACK AND IT LINED UP PERFECTLY
Yes! Unfortunately yes! I have yet to convince the wizard college to spit them out again. I fear at this rate they will be digested and I’ll lose the whole flock
This ceramic sculpture is for the UPwithART fundraiser supporting Unity Project London and Museum London in Ontario. :)
You can view all the work in person from April 17th-25th. This piece is up for auction to support those in the city experiencing the housing and homelessness crisis.
INCREDIBLY CONCERNING SPIKE IN ANTI-BLACKNESS IS HAPPENING RN.
Some of yall may have heard some of the shit that has been going on right now. I'm gonna give a quick run down of some of the stuff that has been happening. Note, this is not all, and it may never be all as much as I will try to update this.
(I am going to try and compile and briefly explain these as much as I can. There may be misinformation. Please inform me if I got something wrong.)
(This will also be updated with additional information and new topics added.)
1) Racist Chinese Dolls.
There are these dolls in China that are being called "Natasha" baby dolls. These dolls are not only very obvious caricatures of black people, but they are being advertised as a "stress relief" in which the people who buy these abuse it in various ways.
This links to a video of a compilation of the various "uses" of the doll. There are more in the replies of the tweet. (Another link to the same tweet just incase)
2) The Mocking, Abuse, and Dehumanization of Black Children.
Apart from the aforementioned doll, there are apparently people going around mocking, abusing, and dehumanizing black children.
Some people have compared black children to the doll.
Others have been going into African countries and have found ways to mock, abuse, and dehumanize black children for clout.
(Source 1 + Full Video) (Source 2)
There are more videos surfacing.
3) Black people are going missing.
Black people, especially children and teens have recently been going missing at an alarming rate. Some of these same people are turning up dead, deaths being ruled as "suicides."
While it generally unknown why many of these people are going missing, many suspect that their disappearances, deaths, and even lack of coverage is rooted in anti-blackness.
The following is a list of black people that have been reported missing as of recently. Please note that this is not a complete list (it may never be completed due to the fact that many of these disappearances will still occur as time passes) this may contain inaccurate information. Please inform me if that is the case.
By the time you see this, some of these people may have already been found either alive or deceased. This post will be updated overtime.
It is also heavily encouraged that you reblog this with more links to recent cases of missing black people if you are aware of any that aren’t included on this list.
We had one of these in the planetarium the other day!
Honestly he was a very Well Behaved guest who snootled around the lobby before politely leaving when we opened the door for him. 10/10. Definitely prefer this lovely gentleskink over the lady who showed up a day early for a show and blamed us for her failure of reading comprehension.
For anyone wondering: it's called Hyalinobatrachium dianae, and Kermit Frog is one of its actual recognised names (alongside Diane's bare-hearted glass frog)
This however isn't a recent discovery as it was first found back in 2015