Rewatching Treasure Planet (great movie, watch it) made realize something about the way that stories convey information to their audiences. There's been a lot of discussion on the overuse of plot twists and how many stories prioritise surprising their audience over telling decent stories. However, if you instead reveal the "twist" to the audience before it becomes known to the characters, you can build tension and stakes.
Treasure Planet comes right out and tells you that Long John Silver is the main villain almost immediately after his introduction (And even before he's introduced we're warned about a cyborg, so you'd have to be pretty dense to not put 2 and 2 together and realize he's a bad guy). So when the audience watches him and Jim bond and grow closer, it builds tension for when Jim finds out and it highlights the tragedy of their friendship, because we all know it's not going to end well. Then, after the truth is revealed, stakes are created because we want the friendship between Jim and Silver to be repaired, because we know it was real, but we don't know if can be after what Silver's done. And all of this would have been lost if Silver's true nature had been a cheap plot twist. The tragedy would be completely overshadowed by the surprise and betrayal, and any investment in their relationship would have been built on the false impression that Silver was a good guy.
Another good example of this is Titanic. Even if you were somehow ignorant of the ship's sinking, the film makes sure you know that it sank with its framing device of Old Rose telling her story to people salvaging the Titanic's wreak. And Titanic's plot structure could only possibly work if you know the ship is going to sink. I'm not just talking about building tension, tragedy, and stakes for the characters like with the above example, I mean that if you didn't know that the Titanic was going down walking into the film, the abrupt shift from romance to suspense-disaster would be an increadibly tough pill to swallow. But it works because we expect it. You don't walk into a film called Titanic without expecting the damn boat to sink.
However, the sad thing about both of these examples, is that despite all the benefits that came from telling the audience these things ahead of time, I think the main reason the creators didn't make them plot twists was because they couldn't have. Treasure Island is the single most influential piece of pirate media out there, and you'd have to have been living under a rock for over a century to not know the Titanic sank. So, the writers had to work around the fact that these important turning points in the narratives were common knowledge, and they wound creating incredible stories as a consequence.
I want to see more of this style of writing in stories where the writers aren't forced to do it. We've clearly seen that you can tell some really damn good stories by giving information to the audience before the characters learn it, and I just wish more works would do that instead of trying to surprise people with shocking twists.
This is also why most adaptations of The Strange Case of Dr. Jekyll and Mr. Hyde don't follow the mystery plot structure of the original book, since everyone already knows they're the same person, no one will be surprised by that twist nowadays.
As a consequence, most adaptations of the story are told mainly from Jekyll's point of view, and the conflict between Jekyll and Hyde becomes the main story, which makes for really compelling drama!
We are now having a very innocent little chat. Let’s suppose that there is a bomb underneath this table between us. Nothing happens, and then all of a sudden, “Boom!” There is an explosion. The public is surprised, but prior to this surprise, it has seen an absolutely ordinary scene, of no special consequence. Now, let us take a suspense situation.
The bomb is underneath the table and the public knows it, probably because they have seen the anarchist place it there. The public is aware the bomb is going to explode at one o’clock and there is a clock in the decor. The public can see that it is a quarter to one.
In these conditions, the same innocuous conversation becomes fascinating because the public is participating in the scene. The audience is longing to warn the characters on the screen: “You shouldn’t be talking about such trivial matters. There is a bomb beneath you and it is about to explode!”
In the first case we have given the public fifteen seconds of surprise at the moment of the explosion. In the second we have provided them with fifteen minutes of suspense.
The conclusion is that whenever possible the public must be informed. Except when the surprise is a twist, that is, when the unexpected ending is, in itself, the highlight of the story.
--Alfred Hitchcock, on the difference between surprise and suspense.
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.
"While those working at private companies can at least earn a little money, they face possible punishment if they refuse, from being denied family visits to being sent to higher-security prisons, which are so dangerous that the federal government filed a lawsuit four years ago that remains pending [note: article is from 2024], calling the treatment of prisoners unconstitutional.
Though they make at least $7.25 an hour, the state siphons 40% off the top of all wages and also levies fees, including $5 a day for rides to their jobs and $15 a month for laundry.
Turning down work can jeopardize chances of early release in a state that last year granted parole to only 8% of eligible prisoners — an all-time low, and among the worst rates nationwide — though that number more than doubled this year after public outcry."
No state has a longer, more profit-driven history of contracting prisoners out to private companies than Alabama.
[Image description: Post from the ABoringDystopia subreddit, titled "In Alabama, McDonald's and other businesses can 'rent' prison inmates...". The post is a picture inside a McDonalds; a Black person, facing away from the camera, is chained by the ankle to a table. End ID.]
Not specific to McDonald's, but I recently wrote a paper on prison slavery in the US & I wanna recommend the ACLU's report from 2022 on this system for anyone looking to learn more:
Captive Labor: Exploitation of Incarcerated Workers, an ACLU research report produced in collaboration with the Global Human Rights Clinic o
[I]ncarcerated workers typically earn little to no pay at all, with many making just pennies an hour. It is rare that a job pays more than a dollar an hour—even the incarcerated firefighters braving the flames that rage across California’s forests and hillsides year after year are compensated at $1 an hour. Even so, many consider themselves lucky to receive these low wages. That is because, in seven states, incarcerated individuals are forced to work but are paid nothing at all for most jobs.
At the same time, incarcerated workers produce real value for state prisons and state governments, the system’s primary beneficiaries. Nationally, incarcerated workers produce more than $2 billion a year in goods and commodities and over $9 billion a year in services for the maintenance of the prisons where they are warehoused. Even though prison labor is not what is driving mass incarceration in the United States, incarcerated workers’ labor does partially offset the staggering costs of our country’s bloated prison system.
Also, fun fact! In 2018 Colorado actually removed the exemption for prison slavery from their state constitution, making it illegal.
In 2023, NPR published this article which revealed that was still occurring in Colorado prisons, and in fact there was apparently no change even five years after banning prison slavery:
After a few months working in his prison's hot and crowded kitchen, Richard Lilgerose noticed he was having trouble sleeping.
"I was always anxious about having to go to the kitchen and work under these conditions for hours upon hours and not knowing when I was going to be able to go back to my unit to get some rest," he told NPR in a call from prison.
Lilgerose, who has been in prison for 20 years, suffers from PTSD, and says the chaos of the kitchen made it hard to work there. He kept asking for breaks, and eventually the guards stopped making him work. But Lilgerose says they also punished him, moving him to a unit with less access to the outdoors and to phones. He says he also lost "good time," which can determine parole eligibility. [...]
"Unfortunately, here we are five years later, and we have not seen the change happen inside of our prisons. It's been business as usual," says Kym Ray, a community organizer with Together Colorado, a multi-faith community organization. "It was never intended to be a symbolic sort of thing, like we removed it from our constitution with no expectation of change. We actually did, in fact, expect there to be some level of change."
Imprisoned people are often subjected to solitary confinement (which is itself a form of torture that needs to be banned) for refusing to work.
In February of this year (2026), a judge ruled that the Colorado Department of Corrections was violating the state constitution by doing forced labor (by which they mean slavery but we can never just call a spade a fucking spade. if the law itself is about slavery then i'm pretty sure breaking that law should be considered slavery!) Let's look at what they said in their defense!
"We respect the judicial process and continue to evaluate the full legal and operational implications of the court's decision to determine next steps. The Department of Corrections agrees that slavery and forced labor are wrong and illegal and do not believe we have engaged in either," she wrote. "CDOC programs are designed to provide essential skills, vocational training, and rehabilitative opportunities that support successful reentry into the community. The Department remains committed to upholding the Colorado Constitution, and believes we have been despite the ruling. We are also committed to ensuring the safety and security of our facilities, staff, and the incarcerated population."
Wallace said in her ruling that CDOC argued that it "merely provides incentives to work, and withholds privileges from individuals who refuse," and argued "there were no disputed material facts to support the claim CDOC subjects incarcerated persons to involuntary servitude." [...]
"Governor Polis strongly agrees that slavery and forced servitude are wrong and illegal. The Department of Corrections does not engage in either and is always interested in how prison reforms can better ensure that this never occurs in Colorado. The Governor's Office is reviewing the judge's order to determine next steps."
So, they tooootaalllllyyyy didn't do slavery guys, they LOVE not doing slavery so so much, and they just always want to be making prisons even better so that all the slavery they aren't doing doesn't happen, and they are reviewing the orders given by the judge who ruled that they had broken the law about not doing slavery to ensure they will continue never having done slavery better in the future!
From that first NPR article, this professor put it pretty cleanly:
"It's not clear to me that in any state where that amendment was adopted, that the Departments of Corrections actually said, 'Oh, OK, it's our understanding that we will not force anybody to work again,'" she says.
This isn't just a "repeal the amendment" situation, we truly need some deep systemic and cultural change to actually abolish slavery once and for all (and all of the institutional civilizational forces that allow it to exist and be justified).
Danny Phantom x Over the Garden Wall crossover | Finale...
Part 1 | Part 2 | Part 3 | Part 4 | Part 5 | Part 6 | Part 7 | Part 8 | Part 9 | Part 10 | Part 11 | Part 12 | Part 13 | Part 14 | Part 15 | Part 16 | Part 17
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