I support the Axis of Resistance (Death to israel)
@abolish-the-draft
They/them | aro/ace | writer | YouTuber (Snickle Fritz) | into: Epic: The Musical, Hazbin Hotel, | Currently writing a musical adaptation of Paradise Lost | Fully intends to kill every TERF/radfem on this site.
if u call urself a misandrist I'm going to assume ur homophobic. I'm gonna assume that ur at the very least weird about trans women like me, that you're going to judge them based on how they pass, on how out they are, on what level of transition they are at. I'm gonna assume ur racist too. like. idk "misandry" very feels like the sorta "feminism" someone is really into when they're in high school and carefully making sure to never think about anything.
and do you believe yourself to be an unfailing arbiter of who that is? and is it truly all cishet men? do you hate POC men, if they are cishet? what about intersex men? why not just hate bigoted people? why find groups of people, groups big enough to undoubtedly contain marginalized people?
"trans men have male privilege!!" this "trans men have female privilege!!" that. chat i thought we all knew that trans people dont have ANY privilege because. you know. they are TRANS.
This comment was made in reference to theater kids idea of being progressive, but I also think it applies to the majority of Tumblr users.
A lot of y'all coast on your queer identities and assume it goes without saying that you're as progressive as it gets while being completely detached from the material realities of people in places like the global south. Y'all are just in your own little world here, debating who does and doesn't have privilege based on which marginilized identity they belong to.
You tolerate zionists because to do otherwise would be "playing into anti-semitic stereotypes" or some shit, material realities of Palestinians and Lebanese be damned. Thay's how much of a joke the politics are here.
I'm glad to see the Michael movie has spawned a whole new generation of MJ fans. I would just like it to be known that I have seniority here. I was binge-listening to his entire catalogue back in 2011.
for people who can’t watch the video: THE AMYGDALA CHANGES TRADITIONALLY FOUND IN MOTHERS SHOW UP IN ALL PRIMARY CAREGIVERS REGARDLESS OF SEX
Changes in this part of the brain were previously used to previously used to argue that women are the ideal primary caretakers of children in all cases. And apparently, it’s false. The reason they found these changes in women was that women were already the primary caretaker in almost all cases, not because there’s something inherent to women that makes them better parents.
This is also big news for adoptive parents and queer couples! Many people try to argue that adoptive parents aren't real parents because of biology and blah blah blah. Bigots will also argue this case against queer people. So, to all my traditionalists: it's not science! It's bigotry and sexist!
This is why paid parental leave for all parents regardless of gender is so crucial. All parents need and deserve time to bond with their children. When only one parent is given parental leave, that parent is naturally going to have more time to develop a bond to that child than the parent who immediately goes back to work. This will, inevitably, create a lifelong imbalance in who does most, or all, of the childcare. Equal paid parental leave regardless of gender benefits all parents and all children.
If you claim yourself to be a feminist, please repeat this after me:
The.
Patriarchy.
Is.
Not.
Natural.
Or.
Biological.
Please, I am BEGGING you. Understand this. Humans have not evolved for patriarchy. The assholes who tell you that do so to uphold the patriarchy. It is the patriarchy trying to claim so. Athropology is VERY CERTAIN that humans have not evolved for this. Humans have lived in a matriarchal OR gender-equal society till about 12 000 years ago. (After which most humans still continued - just a few started patriarchy.)
Stop spreading this misogynic myth of patriarchy being natural. You are not helping your cause.
How do the so-called feminists who insist on excluding men from feminism not realize they're fucking themselves over?
Like, do I need to explain in simple 2 + 2 terms? Patriarchal socialization traumatizes boys during their developing years, which is why the grow into toxic men. The keys to stopping this are held by feminism as it is about opposing patriarchy.
If you don't include men and boys in feminism, they're just going to be toxic forever.
The problem is people viewing feminism as a static thing and not something with forward momentum. They don't view feminism as a movement to end patriarchy, they view it as a fortification against patriarchy.
I know radfems are black-pilled doomers (I know because I've heard reformed former radfems admit it and claim they became way happier when they stopped hating men and trans people), they genuinely don't believe it's possible to end patriarchy.
They don't read reputable feminist literature, just Catharine MacKinnon and cherry picked Andrea Dworkin quotes. Feminism to them is just wallowing in misanthropic misery as they connect to other radfems in their online echo chambers as they sit on their crumb-filled beds.
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.
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