so i'm reading murderbot again, and i'm having thoughts about parallels between murderbot's experience and chronic pain/illness. the parallels between murderbot and the autistic experience have been well discussed, and chronic pain/illness is one aspect i haven't seen talked about as much.
i'm thinking specifically of the way it is constantly turning down its pain sensors, or in network effect where it is sitting at a display surface, "leaking" and barely able to hold itself upright, trying to accomplish something while it's lost a significant portion of the muscles in its back and chunks are sliding down the chair. it's constantly pushing past pain and bodily injury to get shit done, and to me, that just resonates a lot with my chronically ill experience of being in a state where most people would at least rest if not seek medical attention, but i can't because i need finish this thing and i'd be in pain anyway.
there's also the aspect of murderbot's friends seeing it get shot and/or otherwise injured, and going "hey, maybe we should get you to medical or at least address this somehow", and it had been carrying on, worrying about things it considered more pressing. it just sort of reminds me of say, my partner telling me i should sit down and let them take over making dinner because i was standing there groaning in pain while i chopped vegetables, carrying on because sure, i'm hurting, but we still need to eat, and i didn't think to ask for help myself.
any other chronically ill/hurting murderbot fans see what i'm getting at?
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.
All it means when people say âyouâre speaking from a place of privilegeâ is that youâre likely to underestimate how bad the problem is by default because you are never personally exposed to that problem. Itâs not a moral judgement of how difficult your life is.
blocking tip: you don't have to wait to have a negative interaction with someone to block them. you can block them without ever interacting with them. I can't tell you how many times I've seen someone being rude to someone else and preemptively blocked them
Also, blocking someone isn't a comment on their inherent worth as a human being or the quality of the content they post. You don't have to justify blocking anyone. Block them because they're rude, yeah, but also block them because they harsh your particular vibe. Curate your internet experience.
[Transcription: Speaker is a blue-eyed older man with dark blond hair that falls down his back, a round face, and a moustache and beard combo with some gray hairs amongst the blond. His voice is deep, and a bit choked up at points.]
âThese are my red flags for women:
If she stabs me more than twice.
If she has a concerning amount of ex-husbands who died on their honeymoon, like... [a brief pause for thought] Like four or more.
If Gozer the Gozerian asks me to choose the form of the destructor and then one of my childhood crushes walks through New York City at 300 feet tall, uh, and steps on a church... [takes a breath and pauses for a second] I mean, itâs not the height! Itâs not the height. I like a climb. But, like. [another breath] She stepped on a church. Or any building, really, âcause. [deep breath followed by a brief pause] Legally theyâre not supposed to be able to ask you about that on like your homeownerâs association application, but- but theyâll ask. Theyâll look it up.
If she doesnât exist in the same physical timeline as I am... [several seconds long pause before continuing, sounding distraught] Iâm not doing that again.â
#my family does this thing#when we've majorly unfucked a room or done chore that we were putting off#or whatever. Any sort of household Improvement.#'Come brag on me.'#I means come look I cleaned/rearranged/did dishes/put away the laundry#and the scripted response is 'oh nice it looks SO much better in here now'#like my mom did this when we were kids.#'girls comr brag on the garage I finally organized it so I can get my car in there'#and we go and 'ooh' and 'aah' and tell her how nice it looked and how she did a good job#and we could have her 'come brag on' us for like doing the dishes or cleaning our rooms#I do it to my wife now too#it's a dialogue that means#'I did a chore and it feels like an Accomplishment even if it objectively wasn't a big thing. Please acknowledge this.'#and#'Wow you sure did do a thing. It has improved our material circumstance even if only in a small way. Thank you for doing it.'#like yeah scrubbing the pans is my Job and it's a Little Task but sometimes it feels like a Big Task#and it's nice to have an Accepted Script where I can just demand 'I have functioned as an independent adult praise me with great praise' - by @thepioden
Omg, I love this. And it can be applied for brushing teeth. Like yes, you should do it. It's your body to care for. But it's a pain. So for all of you who have brush and/or flossed today. Good job getting it done! It's cleaner now than it was before and it's another step to keeping your teeth healthy and happy.
Sometimes I think peopleâs complaints about queer genre fic boil down to them wanting litfic and not knowing thereâs queer litfic. If you wish to read about sad lesbian adjunct professors having unsatisfying sex, rejoice! NPR has reviewed it for you
i think there are very few popular fandom headcanons i could be more happy to see was a correct prediction on our part than "SecUnit hack is slowly spreading across the corporation rim like a freedom virus". the whole 'rogue SecUnit' thing might've previously been mostly humans' usual fear of slave/robot uprising with a dash of deliberate propaganda but it is very quickly becoming an Actual Issue
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HANOVER, PA -- (BUSINESS WIRE) â Utz Quality Foods, LLC, a subsidiary of Utz Brands, Inc., is issuing a voluntary recall in the United State
Utz Quality Foods, LLC, a subsidiary of Utz Brands, Inc., is issuing a voluntary recall in the United States of certain limited varieties of ZappâsÂŽ and DirtyÂŽ potato chips. This voluntary recall follows notification to Utz that a seasoning containing dry milk powder, sourced from California Dairies, Inc. and supplied by a third-party supplier, may contain the presence of Salmonella. The affected seasoning batches tested negative for Salmonella prior to use; however, out of an abundance of caution, Utz is recalling the limited varieties of Zappâs and Dirty brand potato chips identified [in the link].
This is all of the information I have. I only have the information that I have provided. I only have US-based information. I do not know if Utz Chips are exported to other countries. If this paragraph seems absurd to you, thank the people who were twerps to me about recall posts in the past.
"Sys how is your decent into fiber arts hell going"
Glad you asked. I have arrived at 'modern flax is Bullshit compared to what we had in historical textiles, the flax widely available for handspinning is basically the tow that would be discarded from textile creation and used with tar to caulk ships back in the day'
This naturally led me down a hole of 'why is the staple length of this stuff a bullshit 6 inches' and the answer is 'we have bred modern flax more for the oil than the fiber because cotton usurped the place of everyday textile thanks to slavery and the cotton gin'
Anyway, THIS led me to a rabbit hole that culminated in me finding flax seed bred for proper 30 inch tall plants for fiber, sold by some fellow minded nerds on a website that has not been updated since 1998 and you have to email them to buy anything.
I FAILED YOU ALL here is the site. You can also buy flax fiber from them. The PROPER shit, not the hot garbage ass tow fiber sold as flax top for handspinners.
'machine combing shortens the flax fibers by several inches'
This right here is part of why modern linen is a pale shadow of historical linen. Legitimately it cannot be properly replicated by machines. It HAS to be made by human hands if you want the best quality.
