the childhood abuse history need to spend large amounts of time Unobserved is deeply inconvenient but it being inconvenient unfortunately does not make the need go away
it’s just so crazy that there’s two main metaphors for racism in the stormlight archive, lighteyes/darkeyes and humans/singers, and brandon fumbled both of them like. dude you could have just decided not to talk about racism at all if you didn’t have anything to say about it.
stormlight is so fundamentally about being a white american man that you can read into brandon's metatextual arc into the politics of the series.
kaladin and shallan have two ends of the 'pull yourself up by your bootstraps' story within a corrupt system while dalinar realizes from his position as an embodiment of the system that corruption exists. there are good moments here and good themes, hope and perseverance and don't kill yourself etc. (neoliberal slop)
then we get moash and the parshmen are people reveal. the ambiguity of the moash storyline is what makes it compelling. if there wasn't a case to be made from both sides then it doesn't work. the audience needs to be with kaladin all the way through even as he helps and then ultimately betrays moash. parshmen slaves being full sentient beings is a slight subversion of a sort of house elf trope, but not unexpected. we have had rlain the whole time as a tease that things are not what they seem.
oathbringer is where it all comes together to get to the point where reality and fantasy are almost merging. humans conquered the continent and subjugated and exterminated the natives and their culture. your way of life, even if you can't abandon it was built on genocide and slave labor. can you still participate in that and consider yourself a good person?
and then RoW shows that Brandon isn't ready to write these books. he regresses back into fantasy, dropping the ball on the moral rolling stone that has been building momentum since minute one. all nuance is written out and it becomes a straightforward fight between good and evil.
the way odium and the fused were written means that any doylist critique can be given a watsonian answer.
q: should the land of the continent that was violently conquered be given back to its original inhabitants?
a: no because they worship an evil god.
q: when, if ever, is revolutionary violence justified?
a: never, he told his best friend to kill himself.
this is the frustration. brandon sanderson is not ready to reckon with the answers to the questions that made the first books so compelling. he is not ready to admit some systems might need to be overthrown. he set up for a grand slam and then bunted.
This month people have been tearing Flock cameras off their poles.
This month people have been tearing Flock cameras off their poles. Perched above public streets, they are birdlike things, weatherproof, and they photograph every passing car and file it in a searchable national database.
Somebody cut two of them in half at Washington Avenue and Westcott in Houston, spray-painted the wreckage, and left an American flag on one of them. Police were notified on the morning of the Fourth of July.
Somebody severed a camera in Rutherfordton, North Carolina. The police department posted the photograph itself and collected more than twenty thousand comments. “Not all heroes wear capes.” “Give them a medal.”
Here is what the cameras do when nobody cuts them down. Cops use them to hunt immigrants and to follow ICE targets across state lines and to find women who ended pregnancies in states where that is a crime and to watch exes and to watch women they want, without a warrant and without a judge. A cop types a reason in a box and the box does not check.
A man in Burleson, Texas, told deputies his girlfriend had taken abortion pills. He showed them the photographs, the FedEx envelope, the instructions. Deputies opened a death investigation into a non-viable fetus, and the district attorney told them the state could not charge her, and they searched anyway: 83,345 cameras across 6,809 networks, a month of everywhere she had been. The reason they typed was had an abortion, search for female. The search reached Illinois and Washington, where what she did was legal. They found her in Dallas.
She came into the sheriff’s office a week later, and they thought she had come to explain the fetus, and she had come to report that the man who called them had put a gun to her head.
A sheriff in Jerome County, Idaho ran his wife’s plate more than seven hundred times in three months. He typed the same reason every time. Test. The attorney general found nothing to charge him with. He retired in April.
The Institute for Justice counts at least twenty-two officers who used the system to track people they were romantically interested in, and calls that almost certainly an undercount.
And the cameras keep falling.
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.
buzz aldrin and neil armstrong liked to do a thing where they’d tell unfunny jokes at parties about being on the moon and when people were confused they’d go “guess you had to have been there”
The idea of a popular teenage subculture where girl & boys pretty much all dress the same feels impossible now but for a while it was reality and it was beautiful.
Please save and share this info where possible. This report has since been removed by Amnesty International due to legal threats of libel from JK Rowling. This information is no longer easily accessible.
I'm still thinking about the guy who saw me realize my wheelchair wouldn't fit in the elevator because he (also a wheelchair user) was already inside it and immediately quipped, "This elevator ain't accessible enough for the both of us."
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