Even stars burn out

Ness | Mexican | Any pronouns | Very into TOH, Arcane, MP100, Fire Emblem, Saiki K, WTNV and TSC | Eng/Esp. I run a queue so if you see me posting, I might not be online. Pfp by: @hanelizabeth

[invjayvikzine]

[MOD INTRODUCTION]

Employee NSAR-283, @thousand-winters, brings a love of mystery and carefully crafted storytelling to the Archives. Their commitment to honouring this investigation through writing is exactly what this project needs.

[thousand-winters]

It's just one thing after another after another after another. But whatever, I've been worseeee. I just gotta cry it out for a thousand years and then I'll be alright.

[tlirsgender]

I feel like . A lot of Being Autistic is giving people way too much benefit of the doubt cause you're trying not to have a social anxiety paranoia doom spiral but sometimes they really and truly just are treating you like that & you have to be the crazy one & be like I know you're fucking lying to me

Like oh yeah no it's not that I didn't notice. I've just been ignoring it. Yknow. Which somehow feels worse and stupider than if I really didn't know any better

[wizardarchetypes]

I used to work with a woman who was extremely nasty-mean to me for absolutely no reason at all. She was generally unpleasant to everyone, but it was obvious to me (and to another coworker) that she had something very pointed against me in particular and made it no secret. It got so bad that I made several official complaints, and my supervisor said, "that's just how she talks to everyone. She's super blunt, but she doesn't mean it! Maybe you're just misunderstanding her tone because you're Autistic?"

Later during my 6-month employee review, the same supervisor said, "sometimes when you correct people, you can come on a little too strong and intimidate or offend people."

We went over the specific instances he was referring to, and I said, "I don't think I was unfair or too harsh in any of those situations. I think I was just straightforward for clarity."

He said, "maybe you don't realize your tone is too harsh because you're Autistic?"

So there it is.

If someone's very obviously singling you out to be outright cruel and unfair, you must give them the benefit of the doubt, because you're Autistic and cannot understand.

If you're being straightforward and normal, but someone thinks you're being unfair, you do not get the benefit of the doubt, because you're Autistic and cannot understand.

And when you point this out to allistic people, either they don't believe you, do not care, or do not try to understand.

[cowboy]

the laughing cow and the lactaid cow are trans lesbians and that’s the gospel truth

[pigswithwings]

the fascinating thing about being abused is that years later youre gonna be there sitting around going "okay so what now". cause like theres no instruction manual is there

[pigswithwings]

youre gonna be buying groceries and then youre gonna remember you went through all that for literally no good reason and youre gonna go Oh Okay and put paper towels in your bag or whatever

[dustinkcouch]

I should change my number

[luna-azzurra]

A non-writer asked me "but where do you get your ideas" and i genuinely did not know how to explain that it's not a place. it's not a website. it's not a folder. it's that i was on the bus and a woman was holding a paper bag very carefully and something about the way she held it made me need to know what was inside and then i needed to know why she was sad about it and then there was a whole person and then there was a whole story and the bus had already stopped and i missed my stop. that's where.

[thousand-winters]

Society if the endpoint of my anger wasn't always sadness.

[asmogorna]

mean girls stuff .. just wanted to draw how i imagine them so far

[k57mlem]

[justsomeguycore]

shoutout to the nonbinaries who are like. vaguely cis but not all the way. diet cis. cis at 50% opacity. like if a woman or man was nonbinary. you can be nonbinary or not, it’s up to you, cause the binary-nonbinary binary is nonbinary

[lujinarchive]

Katara and Sokka

[andhumanslovedstories]

Had a patient who absolutely did not under any circumstances want to be disturbed. This is difficult to accommodate in a hospital but not impossible. However one suggestion the patient offered as to how we could manage this was that before we enter their room, we knock on the closed door and wait for a reply (this is fine). If we did not hear a reply, the patient continued, we should interpret this as the patient not wishing to interact and we should leave them alone. At this point I had to be like, listen, there is nothing I love more than respecting patient autonomy by doing fuck all with them all night, but my dude if i knock on a door and my patient who is attached to no monitoring devices doesn’t reply, I simply have to follow up. because this is a hospital. and you might be dead in there. that’s a really reasonable thing to think in these circumstances. And if you’re dead, they’re gonna fire me AND I’m gonna feel bad. Just tell me to go fuck myself if you don’t want me to come in. I’m so happy to wander off to fuck myself content in the knowledge that you are alive. Anyway I told the patient to just hit the call light periodically to order a drink or whatever and I could use that as my safety rounding. Then I left them almost entirely alone. I like to think they got a good night’s sleep, but I didn’t ask. I can tell you that they didn’t die, so I’m basically nurse of the year.

[our-queer-experience]

[forestgreenandgray]

Hey do you know what rumination is?

Rumination is probably the most common type of OCD compulsion, but I rarely see anyone talking about it. I've talked to multiple people diagnosed with OCD who didn't even recognize it as a compulsion.

Basically, if you have OCD you have terrible intrusive thoughts. They can be about anything, but common themes are fear of being a bad person, fear of hurting someone, fear of contamination. etc.

Rumination is when you get stuck in a spiral. Rumination is when you spend hours catastrophizing, overthinking, analyzing, telling yourself it's going to be okay.

I'll say it again:

Rumination is a compulsion.

Rumination is a compulsion, and that means you have to stop doing it.

I did ERP (exposure response prevention) for my OCD with a therapist! For 9 months! And it did help, but the idea didn't really click until I found this website a couple years later.

And Oh My God. It made things make so much more sense, and I was able to pull myself out of an episode even though I wasn't in therapy or on meds at the time.

Genuinely if you have OCD, or even if you suspect you have OCD, I'm begging you to read some of these articles.

Like this was genuinely life changing for me.

Here are some of the ones that were most helpful to me:

Defining Rumination

How to Stop Ruminating

ERP Exercises for Compulsive Rumination

What to Do When You're Triggered

[moblahblog]

<3<3<3

[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.