vibrantly homosexual

🌈 25 ∆ they/he ∆ nb butch lesbian 🌈 ▪ we are all in the gutter, but some of us are looking up at the stars ▪ trans inclusive • white + able + British

[ratbastarddotfuck]

you have to forgive the printer because it's one of the most machine-ass machines we interact with on a day to day basis. that thing says kerchunk. hardly anything says kerchunk these days. you can't get mad at her when she kerchunks up a little.

[digitalsymbiote]

Crazy that tech has gotten so bad that we're doing printer forgiveness now

[terraswallows]

Smoking absolutely destroys your estrogen.

[loki-zen]

has anyone considered that it was probably her house too. where else was she supposed to put her chintz?

[mtndewpitchblack]

[wizardarchetypes]

u think ocd therapy is impossible to do yourself and that it's all too big to start but you can get workbooks or even just try small things.

a lot of my ritual behaviors are "checking"

self-guided ocd exposure therapy can be as simple as resisting the urge to check if your door is locked more than once and sitting with the discomfort until it passes without engaging in any reassurance rituals.

it can look like sending an email and resisting the urge to re-read it over and over again obsessing over your wording, sitting with the discomfort until it passes without engaging in any reassurance rituals.

some of my rituals are also "avoidance"

in which case it can look like checking your email inbox you've been obsessively avoiding because you're anxious about receiving a specific email you don't want to see.

and YEP! ☝️

sitting with the discomfort until it passes without engaging in any reassurance rituals.

[wizardarchetypes]

!!!

it might be hard to believe, but learning distress tolerance for things like "checking" with emails and door locks actually prepared me for the Big Ones like harm and sexual OCD themes.

I think this article from 2007 is a good introduction to the basic concepts of exposures:

Self Directed Treatment for OCD The Irony of Doing the Opposite By Paul R. Munford, Ph.D.        I remember a movie in which one of the char

that SAID, a lot has changed since 2007! the idea that exposure therapy can (or even should) prevent fears from every happening has come into question!

now the conversation about OCD exposure has turned to training distress tolerance:

...rather than aiming for the decline of anxiety (habituation) during exposure, the inhibitory learning approach to ERP teaches people how to be open-minded toward experiencing anxiety and fear when these experiences inevitably show up. Indeed, fear and anxiety (and other emotions in OCD such as disgust or guilt) are universal and even adaptive experiences, not something that need to be “fixed” or gotten rid of. Most importantly, even if they can be unwanted, intense, and distressing, these emotions and thoughts are safe. From an inhibitory learning perspective, fear extinction (and long-term improvement in OCD) depends not only on learning that feared stimuli are safe, but that it is also safe to experience the emotional response that is triggered by these stimuli.

It should be noted that all of the following procedures are still currently being researched. While there is evidence to suggest that they c

And remember at the end of the day I AM NOT a specialist. I am discussing my own OCD journey and referencing the available material on OCD exposures.

I'm not always right, and I can't know what's best for you.

Which is why I haven't recommended any of the old workbooks I've completed, because some of them are old enough that there are better ones to follow that I haven't gotten to trying yet!

I recommend doing your own reading from OCD-aware organizations:

The International OCD Foundation

The mission of the International OCD Foundation is to help those affected by obsessive compulsive disorder (OCD) and related disorders to li

Obsessive-Compulsive Disorder | Made of Millions Foundation

Obsessive-Compulsive Disorder (OCD) is an anxiety disorder that causes unwanted intrusive thoughts (obsessions) and mental or physical ritua

[calebwittebane]

person typing into google search bar: obfuscate meaning

google ai overview: Understood! From now on, all meaning will be hidden from you, and you'll be forced to wade through the dreary vastness. Whether it's things you've always held dear, or new ideas you've yet to discover, nothing will make sense or appear to have any real value. This could be the beginning of a fascinating journey!

[goodassdog]

[depsidase]

[jellogram]

I should be doing more to appreciate the lack of marvel movies in today's popular culture. I once yearned for marvel movies to have this level of irrelevance. They used to feel almost ozymandian, like an empire that had no beginning and no end. and now tony stark iron man is naught but two vast and trunkless legs of stone.

[mollyjames]

I think a lot of transmisogyny stems from this idea that people are really scared to see a dick. The reason bathrooms and locker rooms and hot springs keep being flash points is because these are all places where if a trans woman is using them, it's possible you might see her dick. A lot of transmisogynistic humor revolves around being traumatized because the subject saw a woman with a penis. And look, to a certain extent I sympathize. I'm not a fan of dick; I dont want this thing either. But if you want to be an ally to trans women, I think a big important step you can take personally is to examine your own reaction to the scenarios I described above, and recognize that a dick is just a body part a girl has sometimes. Seeing it as inherently sexual and/or traumatizing is a major wedge conservatives use to justify their rhetoric

[recoveredcombatsister]

its a real shame we cant talk about gendered socialization as the violence that it is without some fuckass rocking up like "and thats why trans women arent women!"

[recoveredcombatsister]

like children gendered as girls are fed less and given less opportunities to play and make messes, and children gendered as boys are offered less help and given less emotional support, and this is hurting them! but no actually we need to stop trannies from using the womens washroom

[toloveviceforitself]

The thing missing from the transphobic analysis is that children gendered as one but perceived to conform more to the other (or to "fail" at their gendered socialization) tend to get a sampler-pack of the worst of both, plus a bunch of outright abuse on top.

[butchnandos]

verandah. beautiful name for a baby girl.

[pansy2025]

goo goo dolls if they were in dune: and i don’t want the worm to see me

[justalurkr]

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.

[irispurpurea]

This is the paper. It's excellent, highly recommend reading it.

I remember reading about Gebru's firing but I had no idea this was the paper she was fired over.

[kirikomamura]

"life is so hard for men because *starts describing the events of a mafia city ad*"

[kirikomamura]

this happens every day and yet people believe men arent oppressed

[kirikomamura]

many lv1 crooks finding a way to get genuinely mad about this post

[valtsv]

my problem is if i enjoy something enough i will be nitpicking. i Will have things to say about where and how it failed. out of nothing but love straight from my heart. unfortunately this often makes me indistinguishable from a hater who has never experienced joy or kindness. such is the amateur critic's burden.

[valtsv]

all of my favourite things are like beautiful racehorses that trip over their own feet a hundred times. but they get back up again. and goddamn, you should see them run.

[enbaluka-tokyo-drift]

[aliasalias]

when i grow up i wanna be a dandelion