If i worked in childcare and my 6 hours were up i would start putting babies in ziploc bags and shipping them to Turkmenistan listed as endangered fruits and vegetables
professions older than prostitution because i’m so tired of hearing that misogynistic talking point created by a british imperialist witnessing impoverished women in india
1. hunter
2. forager
3. midwife
4. babysitter
5. weaver
6 doctor/healer
7. shaman
8. fisher
9. stonemason
10. navigator
11. sentry
12. butcher
13. cook
14. storyteller
15. woodcarver
16. food tester
17. builder
18. tanner/leatherworker
19. scout
20. fire tender
there is no evidence of prostitution’s existence until the neolithic agricultural revolution, stemming from an unequal resource distribution and the rise of female oppression. for reference, the start of agriculture until now comprises less than 10% of homo sapien history. do not let men tell you misogyny is a natural part of life. it’s not.
american blackbirds are icterids but european blackbirds are thrushes but american robins are thrushes but european robins are flycatchers and they are named robin because (checks notes) brits in the 1400s called them "robert" on account of they are just some familiar guy who shows up in your yard. hold on post canceled is that really why they are called that? what the fuck. they did this with jackdaws and magpies too? i can't even be annoyed. how human. "who's that? that's bob." fuck dude it sure is.
"Because trans men are men and men have male privilege, it's just basic feminism"
"Okay but basic feminism wasn't written with transmasc experiences in mind and therefore doesn't account for our real lived experiences which are contradictory to the theory. Can you give me material examples?"
"I refuse to have to explain something that's just so easy to grasp 🙄 do your own research"
"I have done my own research and it shows that trans men don't have meaningful male privilege"
btw TIMs are in the notes of this post using this as an excuse to rant about how feminism makes them feel unsafe because women might use their AFAB privilege to falsely accuse them of assault.
your movement is built on antifeminism and that’s probably why you are surrounded by people who are hostile to hearing female people talk about how they’re not treated as well as males lol. the problem isnt that feminists exclude you, it’s that you’ve joined a community that demonizes any brand of feminism that does include you.
the rainbow is a well-known symbol of gay pride that originated in the late 1970s in san francisco, when the gay community promised to never again destroy the earth by flood
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.
Item: Banana Boots; -5 Friction on any terrain. While dangerous for the untrained, someone with high enough Dexterity can use them to pull some intricate footwork maneuvers.
it’s crazy how when you’re 11 you think wow nationalism is the root of all evil and war is despicable and religion is the opiate of the masses and misogyny is everywhere and climate change is our most dire threat. and you start to grow up and you think well surely it will become more nuanced to me, surely there must be a reason adults arent breaking down wailing in the streets due to the cruelty of this world. and then you become an adult and you think wow nationalism is the root of all evil and war is despicable and religion is the opiate of the masses and misogyny is everywhere and climate change is our most dire threat
You don’t hate your boobs, your stomach lines, your face, jawline structure, or your nose, you hate how its treated within the context of a patriarchal society. It does not mean you're the other gender, woman, it means you're a victim of misogyny.
If I was JK Rowling and I wrote a plotline in my book series about a race of enslaved people whose horrible mistreatment at the hands of the bad guys is part of what establishes them as bad guys, and there were multiple crucial plot points that involve someone either being punished for dehumanizing them and/or rewarded for freeing them, and the only main character who is okay with their enslavement could not get his happy ending until he realized that he was wrong and aligned himself with freeing them, and the whole thing was a pretty explicit metaphor for the patriarchy and how some ‘tradwife’ women are complacent in their oppression but that DOESN’T make it ok for men to treat them like commodities… and then countless people online criticized me for ‘writing a plotline that excuses slavery’ ???? I would have the biggest crashout of my life. A lot of you like to say ‘Harry Potter was poorly written’ but what you actually mean is ‘I don’t have enough media literacy to understand a series written for children’
how come we don’t see trans men doing this shit tho? it’s always trans women “living the girlhood they didn’t get” but i have actually never come across a trans man wearing little infant boys clothes and talking about “the comfort of a warm wet diaper” because he missed out on boyhood? so drop this lame ass excuse fr
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