If you send a stranger you've never spoken to a message that just says "hey", and don't follow it up with any other words or interaction, you're gon'a get reflex blocked, 'cause that (undercase, unpunctuated, unprompted) random message 100% looks like it was sent by a spambot.
It literally does not matter how much jazz you put into your personalized bio, or if you have a personalized user image-- Random messages sent to strangers without additional "signs of life" look suspicious as fuck.
I’m reading The Deviants War: The Homosexual vs The United States of America and the entire point of gay pride as a concept comes from police raids on bars, clubs, public restrooms, etc where gays were humiliated and outed in the newspapers (sometimes with their addresses!) and had careers ruined and lives upended by being associated with perversion and vice squads and all that and they responded by going “no I’m proud” and took that pride to the streets in defiance of the huge mechanism of shame that existed to oppress the gay community into obscurity and so the fact that people are now trying to apply conservative dogma to pride parades to make them “safe for children” or in other words “safe for people with oppressive conservative values” is simply insane
To phrase this more clearly: “public indecency” laws were the primary tool for brutally enforcing gender and sexual conformity, so applying a “public indecency” lens to pride parades of all things is a slap in the face of everyone who ever suffered under gender & sexual oppression and took their anger (and yes their pride!) to the streets. If it makes you uneasy or uncomfortable maybe you’re not on the side you think you are!
like, the most compelling ships for me always stem out of one thing: the characters have a profound, ongoing effect on each other’s senses of selves. when they are apart, the characters’ actions are still affected by each other. the way they approach the world changes because of the other.
which is this deeply Austenian view of ideal romantic relationships as mechanisms by which we come to know ourselves better and become better versions of ourselves. good romance, for me, is always tied in with a sense of self-actualization, and the way in which a beloved partner allows a person to know themselves better.
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.
Since March, I've been letting this little nest of Guinea paper wasps (Polistes exclamens) live at the back of my patio plant rack because they're good pollinators, and they've been well-mannered 'cause I don't bother them (AND, since I'm out there doing Plant Stuff™ so often, their queen(s) have remembered my face and my voice long enough by now to condition their newest emerging youngins to accept my presence, too.)
All that just to say that these dudes have only been recognizing me when my hair-- long, dark, curly, big --is tied up in a tamed bun on top of my head.
It was like a magic trick, watching them almost instantly stop stomping and wing buzzing when I took a step back (still in their sightline) and piled my hair up with a Scrunchie.
The works of the roots of the vines, of the trees, must be destroyed to keep up the price, and this is the saddest, bitterest thing of all. Carloads of oranges dumped on the ground. The people came for miles to take the fruit, but this could not be. How would they buy oranges at twenty cents a dozen if they could drive out and pick them up? And men with hoses squirt kerosene on the oranges, and they are angry at the crime, angry at the people who have come to take the fruit. A million people hungry, needing the fruit- and kerosene sprayed over the golden mountains. And the smell of rot fills the country.
Burn coffee for fuel in the ships. Burn corn to keep warm, it makes a hot fire. Dump potatoes in the rivers and place guards along the banks to keep the hungry people from fishing them out. Slaughter the pigs and bury them, and let the putrescence drip down into the earth.
There is a crime here that goes beyond denunciation. There is a sorrow here that weeping cannot symbolize. There is a failure here that topples all our success. The fertile earth, the straight tree rows, the sturdy trunks, and the ripe fruit. And children dying of pellagra must die because a profit cannot be taken from an orange. And coroners must fill in the certificate- died of malnutrition- because the food must rot, must be forced to rot. The people come with nets to fish for potatoes in the river, and the guards hold them back; they come in rattling cars to get the dumped oranges, but the kerosene is sprayed. And they stand still and watch the potatoes float by, listen to the screaming pigs being killed in a ditch and covered with quick-lime, watch the mountains of oranges slop down to a putrefying ooze; and in the eyes of the people there is the failure; and in the eyes of the hungry there is a growing wrath. In the souls of the people the grapes of wrath are filling and growing heavy, growing heavy for the vintage.
The Steinbeck quote is important and true, but also I wonder if the peach trees that were destroyed were on a water table that could support them in the first place. I want to know what's happening to the orchard land now.
i support universal free healthcare for one simple reason: if you are diagnosed with a terminal illness you should quit your job. quitting your job is the correct response to terminal illness. but you can’t do that if your healthcare is tied to your job
listen if somebody knows that they will be dead in a years time, and you are forcing them to continue to come into work, that’s fucked up. terminally ill people should be able to quit their jobs and live their last few months to the fullest. i don’t get how that’s a controversial opinion
