identifying a maladaptive coping mechanism is so bitter sweet like that’s great now i know what i need to stop doing. but that’s literally my something
You may think the phrase "He's just a little guy" comes from internet memes, but you would be wrong.
The true origin of the phrase belongs to celebrated author Tamora Pierce, in her 1983 novel Alanna: The First Adventure, when Gary says, "Still—what can Alan do for you? He's just a little guy"(49).
Thus, whenever we say of someone or some creature that they are "just a little guy," what we are really saying is that they are a short redheaded knight-in-training with some sort of Gender going on who will kick your butt given half a chance.
Thank you for coming to my TED Talk. May we all be the little guys we wish to see in the world.
Pierce, Tamora. Alanna: The First Adventure. New York, Random House, 1983.
not using AI genuinely feels like the rest of the world is experiencing some kind of mass amnesia. if someone says they never use it, the immediate response is that can't be true because "everyone" uses it to write their emails or answer their questions. saw a comment suggesting that not using chatgpt to write an essay is "like the 90s". girl I graduated in 2021 and we weren't doing that! how is it that everyone has suddenly forgotten that they were entirely capable of doing these things all by themselves for their entire lives up until the past few years!! am I going crazy!!!
I told someone at this one side job i have to "stop fucking using AI for everything just make it yourself" for little basic ass lists, and another person says, "well then how would you do it?" and i told him "i would use my fucking brain! like i always have! by the time i told AI what i would even want i could have written it three times."
Hey tumblr friends, in case I haven't told you lately, I have no idea what the FUCK half of you are on about and I WISH I didn't know what the rest of you are on about. Great work. Keep it up.
one of the funnier incidents of me assuming someone knew a meme irl was when a new coworker was talking about some woman who got arrested for tax fraud and I went "God forbid women do anything" and he got scared and thought I was accusing him of being sexist, so he started apologizing and saying how tax fraud isn't even bad, actually.
i feel like im a weird age where i got just a blurry glimpse at the world Before. it used to be cold in the mornings and websites had fun games and the search results showed you what you searched for. covid wasn't a thing. can anybody fucking hear me. did i dream it all????
I'm not a prayin' man, but the night I found out my at-the-time-fiancé had been sending sex horny nasty horny sex asks to my friend on THIS VERY WEBSITE, I sat in the car in the parking lot of an abandoned church and watched a family of deer play in the snow, and it didn't quite feel like a sign because that part of Pennsylvania was mostly deer and abandoned buildings and snow, but it felt nice, and once the tears stopped, I looked down at my phone and my other friend had sent me a text that said, "HE'S TRYING TO CHEAT ON YOU ON THE ONE DIRECTION IMAGINES WEBSITE?" and I realized that life is all about your curated experience. A real choose-your-own-adventure deal. I have never seen someone post about One Direction on here in my life.
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.
Honestly, as a German I can not quite understand the obsession of the English speaking world with the question whether a word exists or not. If you have to express something for which there is no word, you have to make a new one, preferably by combining well-known words, and in the very same moment it starts to exist. Agree?
Deutsche Freunde, could you please create for me a word for the extreme depression I feel when I bend down to pick up a piece of litter and discover two more pieces of litter?
ver = prefix to indicate something difficult or negative, a change that leads to deterioration or even destruction that is difficult to reverse or to undo, or a strong negative change of the mental state of a person
der Müll = garbage, trash, rubbish, litter
-ung = -ing
die Vermüllung = littering
ver- = see before
zweifeln = to doubt
-ung = see before
die Verzweiflung = despair, exasperation, desperation
@shiplocks-of-love I don’t think that will happen. The words make perfect sense. I think if German is your mother tongue you get a feeling for combining words, like a
• irren = to become lost (also: to err, to be mistaken; to wander, to stray)
• der Garten = garden
der Irrgarten = maze, knot garden
• be- = prefix with a variety of functions: ¹as part of a compound word, it denotes a processing or change of state; ²as part of a compound word, it denotes a touch; ³as part of a compound word, it denotes a more intensive preoccupation with or thematization of something; ⁴it forms from a noun an adjective with a pseudo-participle form because the corresponding verb does not exist; ⁵as a prefix, it forms a transitive verb from a previously intransitive verb; ⁶as a prefix of a verb, it shifts the focus and thus changes the sentence structure
• lustig = funny
• -ung = suffix turning an adjective/adverb into a noun
die Belustigung = amusement, entertainment, merriment
der Beitrag = contribution, article in a newspaper or magazine, posting on social media, input to a discussion
The thing is, since in German you have to decline/conjugate many words in relation to the noun they are refering to those monster words actually serve a purpose of making the language simpler.
A common example is a (as in any) red wine (ein roter Wein) as compaired to the compound a red wine (ein Rotwein). If rot is an adjective it has to be conjugated: der rote Wein - des roten Weins - die roten Weine - and many more. But it if rot is part of the noun you only have to decline Wein: der Rotwein - des Rotweins - die Rotweine.
So, die Verzweiflung über die Vermüllung der Umwelt is way longer than Umweltvermüllungsverzweiflung and you would have to know three grammatical genders and the words’ respective declinations. Whereas for Umweltvermüllungsverzweiflung you only need to know that Verzweiflung is grammatically feminine (die) and its deklinations.
do you think the catholic church effectively utilized wokeness by funneling money into the colonization and rape of the americas after issuing the doctrine of discovery which effectively legalized the subjugation of indigenous peoples?
The Catholic Church served a very large role in the transatlantic slave trade; both acting in utter complacency to the practice despite holding the immense political power to stifle it, and participating in auctions and creating loopholes to keep enslaved Christians enslaved purely because they were African. The Church believed that African Christians were inherently "morally inequal", which allowed them to maintain possession of countless slaves despite the multiple papal condemnations of the enslavement of Christians. Slaves purchased by and gifted to convents were compulsorily Christian as well. There is no room for an argument to be made that the church just didn't emancipate non-Christians; they were all Christian by mandate, and baptized upon arrival.
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