On the small soggy wet archipelago that makes up the modern day united kingdom, sunny days are a rare phenomenon. As such, the peoples of england cherish each and every one, even going so far as to write songs about them in their local music. With sunlight in such high demand, to block it deliberately is nigh unthinkable, hence their cultural confusion at the invention of the parasol.
faggy boy: ever wonder why they call them "cell" phones? it's because they have to $ell. it's subtle subliminal messaging to get you to buy into the machine. i know the truth of the ancient pyramids
30 year old tranny holding back laughter so hard she looks in tears: im gonna brainwash you into my little wife
"Americanization" is a real phenomenon, and how non-Americans should be cautious of it is taught in different countries at school. It's taught in Greece and people from other countries told me their elementary or middle school teachers (using the American grades, to make it make sense to the majority on the site) talked to them about it.
It's common sense here, except for USians, so I'll analyze it a bit more for the dominant demographic here. In a globalized setting, the most dominant culture affects the others and sets the trends. The way our language works, how we think, our levels of politeness and intimacy, and our levels of respect. (flash news, they are going down 😂)
I don't want to imply that there is nothing good in the US. There are plenty of positives in the country. It's just that for the rest of the cultures online it's a constant daily fight to not forget our roots, with the degree US media and brands have permeated our lives. In Greece at least we watch more US American media than Greek media nowadays, and many of our shows are rip-offs of USian ones, with little adaptation to Greek reality and culture.
And to demonstrate the amount of this exposure, a 22-year-old Greek asked me the other day "if something happens we call 911, right?" This might have literally cost them their life, in a dangerous situation! Because all the movies and songs they consumed (not an unusual thing for the Greek youth) were what they knew. And I found a similar comment in this comment thread.
Lots of Americans in the notes failing to understand this post. It's not about not liking the US. It's not about you feeling ashamed or guilty for being American. It's not about you.
It's about American media drowning out native language media all over the world, and workplaces requiring the English language in your repertoire more and more. It's about proper translations and foreign language dubbing of films disappearing because "everyone speaks/should speak English anyway." All of this is leading to the deterioration of native speaker groups of languages worldwide.
In my country, Dutch language courses can't find enough people who want to study the language, while English language courses are overflowing with people who want to study the language. There is even widespread distaste for the Dutch language for being crude or sounding rough or what have you. That's our native language!!! That is our culture in its purest form!!! That is knowledge we inherit from our parents as they did from theirs!!! That is how we learned fairytales and folk stories and myths!!! That is the language that shapes our communication and our way of thinking!!! To hate your native language is to hate yourself at the deepest level.
And yet it's so normalised. Droves of foreigners living in the Netherlands will never learn a word of Dutch, because "everyone speaks English anyway." We are the world's leaders in non-native understanding of English, but it comes at a cost. A grave cost we will continue to pay.
If you're looking to support your non-American friends in any way that is not performatively shouting "I hate being an American" into the void, first of all, unlearn that hatred of yourself and your culture. You are of no help self-flagellating, and there is a difference between holding your country accountable for its issues, and denying yourself your culture because your country is doing and has done bad things.
(I am not going to get into arguments about whether or not US American culture exists. It does, and if you think differently you are welcome to change your mind.)
Secondly, learn about other countries. Learn a bit of Chinese. Take an interest in the Italian political system. Ask your friends about their countries' folklore. Watch documentaries about art from Nigeria. Absorb information that is not fed to you by American media.
And thirdly, quit expecting your non-American friends to communicate in a way that appeals to you. The French and Dutch will always seem rude to you because our way of communicating is far more direct than the way you communicate. People from other cultures may seem vague to you because their way of communicating is far more indirect, and you're not used to that either. Quit being frustrated when you don't get what we mean exactly. Quit assuming we mean the absolute worst thing you could imagine just because you didn't get what we meant the first time. Ask us to explain if you need us to, and learn to accept that we are different from you.
We are already adapting to your culture 100% of the time we are online. It's your responsibility to adapt to us, too. At least do your friends the courtesy of learning about and adapting to them.
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.
a talking point i often see when defending the consumption of dark content is that it’s a coping mechanism for those with trauma which is very valid and true but i also want to make this abundantly clear: you can like dark content for no reason. you can enjoy fucked up shit in fiction because it’s enjoyable and entertaining. trauma is not required as a ticket for entry. enjoy your dark content bc it’s fun and sexy and don’t let anyone take that away from you
Imagine if we did the “public libraries are punk” thing for other subcultures. Imagine if people made shirts that said “Soup kitchens are grunge” or “Mixed Use Urbanism is Juggalo”.
C compiler is a dog. it does whatever u tell it to no matter if that ends up hurting it
Rust compiler will put u on a leash theres a reason the main feature of the lang is called "ownership" omfg. she will ensure u follow her every command and she will tell u exactly how to do it safely and how to do it well and shes nice about it
zig compiler is a robotgirl it will not only give u the result u tell it that u want but also follow ur exact instructions on how to get there
C++ compiler is Cs chuuni sister, she will yap about some insane shit and pretend that shes the coolest thing ever but shes a still just a dog at the end of the day
The go compiler will pout and cry because you have an unused import somewhere and there's no way to make it stop except either using that import or taking it out
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