if you vote me for president i vow to make everything the ocean again. no more land only ocean. this will solve all of our problems and replace them with new, far more interesting problems
Someone once said to me, “I hope the pain eases soon.” It struck me as the purest blessing that had ever been offered over my head - I hope the pain eases soon. It’s so gentle, so kind, so hopeful. So to everyone who’s hurting: I see how hard you’re trying, and I hope your pain will ease soon.
just watched jurassic park and from a meta perspective im thinking sadly about how the behavior the carnivores display is way more indicative (at least to me) of wanting to play and lacking stimulation in their lives than actually wanting to eat the human characters. and they got so so demonized for it
JP dinosaur behavior analysis with a healthy dose of headcanon included from someone who doesnt know much about behavioral science. for funsies
ok so first of all lets start with the t rex. her very first moment is the goat leg ending up on the car, but we can see in the next shot that she is very capable of swallowing the goat whole. so how did that leg get there? given evidence that t. rexes were likely social creatures, i like to imagine that the leg on the car was more “here you go have part of my meal because you’re small” for the humans
next is her communication. i want to look at one specific thing, which was actually the thing that prompted the post
to me, that certainly looks like eye pinning. eye pinning is a behavior in birds that signals high stimulation. here’s what it looks like in a bird
it can be positive or negative, but in this case it’s probably not negative, because there’s nothing forcing the rex to stay there. if she wanted to leave the situation she could hit the bricks
the continual roaring also sort of suggests play behavior to me. there’s not really any sense in making a shitload of noise at your prey (unless you’re trying to scare them out of cover, but we know she doesn’t need to do that because we see she’s strong enough to just break into the car) so, especially because they keep screaming, that reads way more like “im making noises and they’re making noises back ^w^” then it does as trying to intimidate prey for some reason
play behavior also makes sense because we know, canonically, she’s crazy understimulated. alan grant says as much when he mentions that they aren’t feeding her in a way that promotes hunting behavior. the way she noses at the jeep and spins it really just looks more like curious interaction than anything, as well as all the chasing people she does
next, the raptors. their really famous scene is the kitchen, but first let’s establish some facts about them. we know from muldoon and what we’re shown that:
- they’re smart enough to use one of their own as a distraction for flanking maneuvers
- they’re good at problem solving enough to wait until the electric fences are turned off to systematically test them for vulnerabilities
- they’re absurdly fast. “60 mph on open ground” fast
- they are absolutely not in a big enough enclosure
- they’re not fed in a way that promotes hunting behavior either
so when you put all this information together and then look at the kitchen scene, i don’t believe for even one second that the “hide behind the counter” routine is fooling those two raptors for any time at all. that entire sequence of loudly scrambling around the kitchen while something that can keep pace with a cheetah pretends it can’t catch you? yeah that makes WAY more sense as play behavior than it does hunting, especially since we see numerous times that there are many things on the island easier to catch and eat than a bunch of skinny humans (this goes for the rex, too!)
the bit with the noises is also true here. more true, if anything. muldoon tells us the raptors are ambush predators, so why on earth would they get into a hunting ground and then risk scaring their prey off with the loud barking calls? “hi we’re here come out and play” is a much more sensible use of a call loud enough to hurt a human’s ears from across a room in that situation
in conclusion: damnit john your girls are bored as fuck. give them a horse ball or a frozen pumpkin stuffed with meat or something
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.
There is a quality of books (or movies or shows) that I can best describe as “stickiness,” which is separate from being good or even enjoyable: a sticky book is one I just keep thinking about. Sometimes it’s because a book is very good (e.g. The Locked Tomb), and sometimes it’s because a book is very bad (e.g. ACOTAR), but there are also very good and very bad books that are slippery, such that when I’m done reading them they slip from my thoughts like water from a hydrophobic surface.
stormborns
dailybridgerton
izzy806
areudirty
janainaart
theartofmadeline
