As a former librarian I'm actually required to remind you that many libraries that subscribe to Libby are opted into a program that lets you subscribe and access magazines for free with no wait
And that this is actually a really fun, low cost way to not only access news and larger cultural magazines, but also to get free patterns for many different crafts that you can screenshot if need be and that lower the financial barriers to entry for trying new things
From my experience working in both academic and public libraries, many libraries are use it or lose it funding-- I have to say this because a lot of patrons feel guilty for how much they use the library and how often they're using it funny enough, but the worst thing you can do for libraries is not try out new features and not use what's already given to you as much as possible.
The numbers that come as a result of your patronage are how most libraries justify their continued existence in times of financial hardship, which sucks but, go check out some magazines on Libby!
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.
for those wondering why they're free to take now, it's because the company that made those "chicken soup for the soul" books bought them a few years ago and then completely collapsed so bad they couldn't afford to dispose of or even take the blu rays and dvds out of their kiosks all over.
so any of them is free game because they're all located on other business' property and they usually don't want to have to pay to get rid of them either. so asking the store manager usually gets you the ok to pull it out and keep it.
there was a period of time right after their bankruptcy where you could put in any debit or credit card and it would spit out movies without charging you. you could even put in like an expired or deactivated card, or a visa gift card with a $0 balance, didnt matter, they'd just start spitting discs out. a lotta people raided redboxes for movies for a couple months, with some people doing what me and my brother and my dad did here, taking the whole box and signs and marquees as well. because managers sure as hell don't want a big abandoned piece of trash on their sidewalk disappointing customers. BUT they're also often too cheap to pay someone to remove it. so they just sit there.
luckily there are no shortage of freaks like us who will just take them away on our own volition. we did it all "by the book", too: we set up cones and caution tape, disconnected electricity properly, used an angle grinder to grind down the bolts in the concrete so nobody would trip on them, then cleaned everything up afterward and sealed off the electrical panel so the store would know everything is safe and tidy. though they were hesitant when we were first contacting them, they were honestly very relieved and grateful when we finally took it away, especially once they saw that we "knew what we were doing" (we don't) and look like we've "done this before" (we haven't).
the fun part: the reason why this redbox, in particular, was completely full and unraided is because the computer hardware inside had failed some months before the bankruptcy, and a failing company sure as hell wasn't gonna send a tech out to our podunk dipshit city to fix it, so it was impossible to rent movies or take any discs out. plus, for who knows how long, people were returning old redbox discs to this machine and not taking any out, leading to a much higher variety of movies than your average redbox.
there is a thriving community of redbox hackers and modders out there, as well, creating open-source software for repurposing the machines and not letting their very interesting and robust disc-management hardware go to waste. this one belongs to my brother (who was very annoying persistent and did all the legwork of contacting managers and securing permission) who is a programmer by trade and will be hacking it into a family-access movie library, with whatever discs we want. i mean the machine is completely weatherproof and has a built-in AC unit, it would be such a waste to not try to turn it into something cool.
if we get another one, i'm gonna try to mod it into some sort of art or zine vending machine. the disc boxes are just the right size for small print art or stickers. would make a great "little free library" too.
remember: the rules are made up. act like you belong there and you can get away with anything. this applies to your own life
Does anyone have the fucking tiktok video of the overly enthusiastic rich bearded guy showing off his new hiking shoes in his Mansion and the Woods, but then another dude duets with it to make it look like he's escaping from being held prisoner please please
