"im not saying feminism is for everyone but-" the fuck? well im saying that. feminism is for everyone. yes even cishet men will benefit from feminism and cishet men should be feminists because cishet men are indeed harmed by the patriarchy; nowhere near to the extent that women are, but having a culture that is fully equal and anti-misogynist benefits everyone. have we forgotten that lifting up the disenfranchised people in society helps all of us as a collective? "im not saying that universal and unalienable human rights are for everyone but-" YES THE FUCK THEY ARE LOL
For three decades, Daniel S. Williams documented Juneteenth and Emancipation Day celebrations across the country — which included parades, cookouts, and other gatherings.
Photos in “Daniel S. Williams and the Art of Bearing Witness” (2023)
“Why are people dropping they/them from profiles” “a lot of people have stopped being nonbinary” “i feel like a lot of people i knew who were nonbinary identify differently suddenly” its the violent exorsexism in larger society and within queer communities that happens like clockwork when there is a rise in anti-queer, anti-trans bigotry.
When fascism spikes, we get a two-fold where folks who cannot or will not assimilate are pushed by our oppressors to reconsider, and fellow queer/trans folks become some of the most aggressive enforcers of that “choice” in an attempt to buy safety within the majority.
This shit is why inter-community discourse is not just petty complaints—the refusal to hold solidarity with the weirdest, loudest, most visible queers in our midst is fascist as well as self-destructive. People are being forced into the closet, forced into labels that make others—including queer and trans people—more comfortable, because comfort and conformity becomes the biggest priority for many when shit hits the fan. And these are the scenarios that dont end up with nonbinary people dead.
You are abandoning the most vulnerable while preaching about privileges, and this saboteur mentality will not even ultimately save you when eventually you are either forced to learn that you do not fit how you thought you did or our oppressors shift the goalposts until even your presentation of sexuality and gender are not “normal” enough anymore.
thinking about “you haven’t met all the people who will love you” and like!!! you also haven’t found all the things that will make you happy!!!! there will always be new authors and musicians and artists whose work you will one day discover and love!!!! there will always be new hobbies and skills for you to learn and feel fulfilled by!!! there will always be new things around the corner that will bring sudden and unexpected happiness!!!!!!!!!!!
given the current climate this pride especially i feel i must mention that i love my trans friends, i stand with trans people in the fight against transphobic legislation and those who would enforce it, and this blog is not a good place for you to be if you do not vibe with that
This version of the progress flag legitimately looks so nice
Gilbert baker rainbow, huge intersex circle, the design is cluttered but in a good way 10/10
[ID: A version of the progress pride flag with a large purple intersex ring outlined in gold, looping through pink, blue, brown, and black chevrons on the side, which have a base of white. The horizontal stripes are: pink, red, orange, yellow, green, light blue, dark blue, and purple. End ID.]
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.
Oh youre "nonbinary"? Can i put you in a box please. Can i pleaseeeee put you in a box. We have two boxes and i really wanna put you in one. But dont worry. My boxes are very Woke and Nuanced. So its fine to put you in one. Pleaseeeee. Wow... youre such a bitch... not letting me put into one of two nuanced and essential necessary boxes... you obviously go into the box all those evil bitches end up in
police departments love to be like "we need more money to fight all the crime that's been happening lately" and they show a graph with crime going up at then you look into the numbers and it's like "the ten percent increase in crime was correlated with a ten percent increase in active policing hours" and it's like oh okay so the crime factory needs more money because the crime factory stayed open late to manufacture more crime in order to convince us to give more money to the crime factory. Where can I get off this carousel of misery?
police departments love to be like "yes, we ruined the lives of thousands more young black folks, but you have to understand: we wanted a tank, and you weren't giving us new-tank money."
contrary to popular belief not everyone has an innate sense of internal gender or care to have one or seek a name for it, some people go their whole lives without questioning their occupation in one of two gender roles, but for some people, if pressed, they don’t feel that internal sense of ‘i am a woman’ or ‘i am a man’, and in that case i feel the switch over to transgender vs cisgender relies on active identification of a gender other than the one they were assigned. if someone’s like ‘idk dude I just work here’ then that’s valid
#i would describe my gender as not exactly ‘idk dude i just work here’ #more like…..when someone assumes you work somewhere that you don’t #but you know how to help them so you do it anyway #my gender is wearing a red shirt at a target
A portion of people in the notes are like ‘but that makes you trans. That’s called being agender’ and another portion of people are going ‘this is how the majority of cis ppl feel and it’s NOT agender’ and personally I feel like both of them are missing the point here. Yes a lot of people identify as agender because of this feeling. Yes a lot of people with this same feeling still identify as cis. These are not mutually exclusive experiences and it doesn’t mean the agender people are secretly cis or the cis people are secretly agender. It just means they have very similar experiences of gender that they choose to conceptualize and label differently, and neither of them are mistaken or wrong to do so.
