My job is at a small urban university library working on Course Reserves and ILL. I have my MLIS, and I am interested in the "cutting edge" of access. The information age is difficult to navigate, and I think librarians are more important now than ever. (she/her; they/them)
I know most of those following me know this, but just to make it super clear. An Gorta Mรณr (The Great Hunger/the Great Famine) was a deliberate genocide of the Irish people. There was enough food grown in Ireland to make sure everyone was alive and healthy and survived. Instead it was exported, sent to England and elsewhere for profit while men, women, and children starved in the streets. While the English landlords fucked off and evicted starving families who couldnโt afford rent. While babies were too weak to cry and died at the side of the road.
They tried to kill us, but they did not succeed. And we owe so much thanks to the other oppressed peoples, in particular the Choctaw Nation and the Masai, who sent money and grain to us.
Let me repeat that. The Choctaw Nation who had just gone through the Trail of Tears sent us money to try save Irish lives. Itโs led to an understanding between Irish people and Native American tribes, most recently when we donated to the Navajo and Hopi fundraisers for COVID-19 relief, because while it may be a different tribe, Irish people will never forget those who helped us and weโll help back.
The entire population of the island is less than seven million people. Weโre still a million less on this island than pre famine. And itโs not that long ago. My grandmotherโs grandparents lived through it. Weโve told the stories, it literally changed the DNA of the country. We have a national fear of renting, because so many people were evicted. People joke about Irish people always offering loads of food, but itโs because thereโs that cultural memory of not being able to.
They tried to kill us, but they did not succeed. We will not let them take our lives, we will not let them take our language. We lost so much, but we will not lose it all.
This is why I get so angry when people say โit was the potato famine, it was because of monoculture/microbes.โ
Nope. The potatoes were the only thing Irish people were allowed to fucking eat, because as pointed out, the rest of the crops they were growing were for their landlords to ship to England. So when the one โworthlessโ crop they were allowed to eat rotted in the field, the English crown, empire, landlords, all shrugged and carried on. People starved to death lying next to productive fields.
hi! carey means needs help still - he's the voice actor for frylock in aqua teen hunger force! adult swim screwed him badly and pays no residuals and barely paid him during the show's run. he has heart failure and survives on con earnings, plushie sales, and donations while waiting for disability to get back to him. posts used to make the rounds for him, but haven't in a while, so i wanted to make a new post!
if you'd rather buy a plushie - here's the shop he and his wife run!
Every time I see bullshit about women never EVER being able to beat men in any sport, I think about how in martial arts classes I, a cis woman, 5' 8" and 145 pounds, regularly beat the tar out of 6' 2" 230 pound cis dude weightlifters. One guy ragequit class. He came in cocky as hell and talking the standard bs line about how a woman simply never could beat a man in a fight because they're physically weaker and our instructor was like. Okay. Put the pads on you're sparring her. Yes, her, the one 4" shorter and 100 pounds lighter than you.
It wasn't close I beat the pants off that man, and others like him. I did it more than once. Some guys got humble and stayed. One guy got angry and stormed out.
And I think about that every fuck damn time I hear that bullshit, which seems to be all the fuck over the place these days. Oh, women are just fragile little soft delicate flower creatures who can't do ANYTHING and could NEVER compete with big strong manly muscular strong MEN.
I think about driving that dude into the mats and seeing the brutal reality of this big dude's misogany meet the realization that a woman was beating his ass literally that second, that none of his strength could stop the fact that I'd just hip thrown him facefirst into the mats and that had I actually connected with the axe kick to his neck I would have crushed a bunch of important shit and he could not stop me, and his whole psyche collapsing like a dying star in that moment.
Anyway, don't ever fall for it, ladies, and there's absolutely no goddamn reason to get your knickers in a twist about trans people in sports.
i think one of the worst things the left wing internet ever did was push the idea that oppression is basically a virtue, and being oppressed is a sign of your morality. it has made it likeโฆimpossible for some of you to hold the idea that most people are privileged in some ways and oppressed in others. AND a lot of you seem to have it in your mind that terrible people cannot be oppressed, and that oppressed people cannot do terrible things, which is a dangerous rhetoric to hold imo.
white tumblr liberals if this site existed in 1800s america: idkkkkk i know slavery is bad but like uh i dont like when slaves say they want to kill plantation owners thats kinda icky likeโฆ.uhh wheres ur empathy..? they are giving you a jobโฆno seriously i know slavery is bad but like if you do a revolt and kill them for raping your women and using your children as alligator bait and skinning people alive to use their body as furniture you will just continue the cycle like youโll be even worse than them! you cant hate them! wheres ur compassion dude they probably feel rlly bad about whipping you it probably gives them bad vibes
I mean, Black people can be Jewish too. And were also victims of the Holocaust as well as other events in Africa committed by Germany that don't really get talked about because the Carving of Africa by European countries gets treated as a footnote at best. So like... He could stay Jewish. That doesn't have to change.
no but im so tired of how self-deprecation is always more accepted than self-advocacy. if i say i can't drive because im autistic i get questioned on how exactly that works and given a million suggestions on how to do it anyway and i look like im trying to be special so it's easier to just say im a loser. yeah i don't drive because im kind of a loser lmao. oh well. and people say lmao back and we move on. at worst they say "oh im sure you'll figure it out haha." but no interrogation!! being a loser is more respectable than being disabled. being a loser is something that doesn't make other people feel uncomfortable about their own biases. so no, no im not disabled. i don't struggle to keep friends and do the laundry and make quick trivial decisions and clean my room and brush my teeth because im autistic. it's because im a loser. it's my fault. it is what it is. at least im funny now. do you think im funny? please think im funny
sexism in medicine kills people. racism in medicine kills people. fatphobia in medicine kills people. queerphobia in medicine kills people. classism in medicine kills people. ableism in medicine kills people.
do not downplay peopleโs fears about being mistreated because they are a part of a marginalised group. it is a matter of life and death and you should be angry about it.
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.
people love the idea of the mean girl nurse pipeline because it problematises medical abuse as a personal perversion rather than understanding it as a product of broadly held ableist values and its like, if this was only about ontologically evil teenage girls choosing to enter a profession because of their unique sadism then you really wouldnt expect to see the exact same forms of abuse pervading all arrangements of paid, unpaid, formal, ad hoc, and familial caretaking as well -- its more comforting to believe the nurse was just a preexisting bad person than that most of the world broadly hates disabled people and will abuse, neglect, and gaslight them if given power over their care
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