Remove immunity and require each officer to carry insurance. The more fucked up the department the higher their insurance and individually it swings further based on claims.
Hit their pocketbooks the way they hit their wives and kids.
was chatting with friends about taste in partners, I said I wanted someone whose weaknesses I could cover and vice versa (I get things off tall shelves, they say I ordered no pickles) and we could sort of mutually protect each other.
these motherfuckers were like "this guy's got a party composition kink"
oh god. that twink pup got into the bear enclosure again. Jessica don't stand there fucking help his hole can't take that many at once he needs a break
The FBI cut the phone lines during the 1977 disability rights sit-in. Then they turned off the hot water.
They locked the doors from the outside. One hundred and fifty people were trapped on the fourth floor. Half of them used wheelchairs. The government assumed they would leave.
Kitty Cone was thirty-three. She had muscular dystrophy. Her muscles were failing, but her logistics were flawless. She knew how to organize people.
The federal government had promised to sign regulations protecting disabled Americans from discrimination. The policy was known as Section 504. They printed the promise on paper. Then they stalled. Without a signature, it was just typography.
The protesters entered the regional Health, Education, and Welfare building in San Francisco on a Tuesday morning. They took the elevators to the director's office. They brought sleeping bags and catheters. They informed the staff they were not leaving until the law was signed.
By sunset, the police surrounded the exits. Kitty sat near the windows. She organized the floor plan. She assigned committees for security and sanitation. She kept her medication in a small cooler.
According to federal memorandums released decades later, the strategy to end the occupation relied on medical attrition. The building was not equipped for long-term habitation. The FBI calculated that a population requiring ventilators, specialized diets, and daily medical aides would voluntarily evacuate if the environment became sufficiently hostile. They instituted a blockade.
The blockade went into effect immediately. No food deliveries allowed. No medical supplies permitted through the lobby. Guards stood at the main doors checking identification.
Kitty's muscles deteriorated faster under the physical strain. She couldn't walk. When the phone lines went dead, the fourth floor lost contact with the press. The government waited for the quiet.
Kitty dropped to the floor. She realized the barricades were designed for standing adults. The police had blocked the hallways at waist height. They hadn't blocked the linoleum.
The floors were covered in cigarette ash and spilled coffee. She dragged her body through it. She crawled under the barricades to reach the restricted elevator shafts and unguarded offices.
She carried notes in her pockets. She found a single working payphone the FBI missed. She called the local news desks. She called the mayor's office.
She crawled back. When her arms failed, someone pulled her by her ankles. The Black Panthers heard the news reports. They crossed the police lines with hot meals. The FBI could not stop them without a riot.
They shut off the elevators, so she crawled.
The occupation lasted twenty-five days. It remains the longest non-violent occupation of a federal building in American history. On April 28, the Secretary of HEW signed the regulations without a single alteration.
The protesters left the building the next morning. They went back to their apartments. The Rehabilitation Act regulations laid the groundwork for every accessibility law that followed. The HEW building still stands on United Nations Plaza. The elevators run on a schedule. The doors are heavy glass.
Kitty Cone: the woman who crawled under the barricades.
A lot of people on twitter wanted me to explain how I draw expressions, so here you go
Unless you're drawing explicit realism, in my opinion, expressions should be exaggerated to some degree. If you aren't doing a 1:1 recreation, the point is to get the FEELING across. Try making the expression you want to draw and feeling how your face pinches and stretches.
Skin doesn't just "disappear" when your face moves it around --- that's where wrinkles come from! Pay attention to where your skin creases when you emote, and use it to your benefit. It's a fine line between overdoing it and underdoing it -- find your own balance.
Ultimately, every expression has a little bit of push and pull, unless your face is completely neutral (and even then, there are still some wrinkles...). Learning to think of expressions as actions and reactions is VERY helpful in learning to draw them without needing a reference, and in learning how to stylize and push expressions based on references as well!
I think a lot of people end up with stiff or unexpressive emotions in their art because they're just trying to recreate a picture instead of understanding WHY and HOW the face is moving --- and it's a tough thing that takes a while to really pick up and learn. Hopefully is helpful in showing a way of thinking about it that can influence your process and approach to emotions!!!
Also, bonus: even without the lines, the planes alone still show a LOT of emotion.
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.
we seriously need to stop conceding to the personhood trap when it comes to abortion rights. is a fetus a person? thats a spiritual question. i dont care about the answer. should another person dictate what someone can do with their body? simple answer: no.
like if a fetus isnt a person it has no right to my body and if a fetus IS a peson it also has no right to my body because there is no other context in which we are required to put ourselves at risk of physical harm to preserve another persons safety or even life.
you dont have to save someone from drowning even if youre a strong swimmer. even in death youre not required to donate organs and that could save several people. you can kill someone if you truly believe your safety is at risk. we dont mandate preservation of life over autonomy in any of these circumstances.
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