Hippie-Geek-Mama Strikes Again
Let's be honest, this blog is pretty much just Star Wars (read: Rebels) trash these days (with a teensy bit of RTD-era Doctor Who, LOTR, Jane Austen, Call the Midwife, and Marvel thrown in for good measure.) Kanan/Hera are particularly dear to my heart.
Lover of meta and sometime fanfic author.
Started writing this post ages ago and decided I should finally get it online. These are links to all my fics and lengthier meta posts, both for Star Wars and Doctor Who. Please note that you must be logged in to AO3 in order to read my fics. Enjoy!
AO3 / Teaspoon
Star Wars Rebels
Kanera Fic
Clarity/Sight - Separate, they’ve both been blind. But together, they can truly see. A fix-it fic in two parts for the episodes Jedi Night and Dume.
Ad Astra Series - Through hardships to the stars. Follows Hera’s journey from Jacen’s conception to birth. (canon compliant)
Synchronicity - Creating moments of profound intimacy in the midst of chaos is nothing new for Kanan and Hera. But Hera discovers afterwards that this particular moment may have unexpected consequences and makes a fateful choice
Binary - During a frustrating morning’s meditation on Lothal, Kanan makes a startling discovery and is forced to face a fear he’s never experienced before.
The Signs - A childhood lesson she hoped she’d never need comes back to haunt Hera, and she isn’t sure how she feels about it.
Ghosts - When the dust on Lothal has settled, Sabine returns to their ship to sleep. She finds Hera there already, who delivers some shocking news.
Dehiscence - An unexpected holo-call reopens wounds, both new and old, for Hera and creates a rift she never intended.
Four Doors - Hera and the Ghost crew return to Yavin IV, where she must confront tough decisions about what her future will look like.
Quickening - Sabine visits Hera on Yavin IV, bringing with her a poignant gift.
Grounded - In the quiet of the evening, Hera takes a few moments to meditate—both for herself and for the baby.
I Promise - When the Rebel Alliance faces its greatest battle yet, Hera is drawn into the fray to help, yet quickly finds herself confronting a crisis of her own.
- Ad Astra Spotify Playlist
Rebels Meta
Jacen Syndulla: Answers to All the Big Questions
Hera and Heritage - A Meta In Pictures
When a Shoulder Touch Says Everything
When Hera Calls Kanan “Love”
Of Father and Daughter
More on Hera Mentions in Lords of the Sith
Kanera in the Junior Novelizations
Doctor Who
Doctor/Rose Fic
Jump 137 - The number of realities Rose Tyler has crossed in her search to find the Doctor again feels nearly endless—until a single jump changes everything.
Dreams of Another Life - Separated from his Rose by the walls of the universe, the Doctor dreams impossible dreams. But across the Void, those dreams may not look so improbable after all.
Fic Rec List
Long Fics for the Rose Tyler Lover’s Soul (fair warning that this list is quite old and has not been updated in a few years—a number of fics are no longer online)
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.
If I ask nicely will people reblog this and tell me what their most common breakfast is? Not your favorite necessarily, just what you have for breakfast most frequently? 🙏🏽
"you don't owe anyone anything" You are a tar pit. Speak for yourself. I personally owe the cafe employees my dishes put away and my friends a listening ear and small scared insects a cup and a gentle trip outside. Hyperindividualism is a rancid infection borne of capitalism and willfully misinterpreted therapyspeak and I will defy it by continuing to be kind regardless of whether or not it benefits me personally
im currently completely losing it about the great stalacpipe organ. are you fucking kidding me they made an organ out of a CAVE???? IT TAKES UP THREE ACRES??? i legit am about to lose it
this is a comment left on a recording of moonlight sonata played on an organ that is literally made out of a cave and its making me so emotional its not even funny
[image id: a youtube comment that reads ‘wonderful…and the moon has never shone there…’ end id.]
According to Wikipedia, it works by hidden rubber mallets on the naturally-musical stalactites that tourguides have been knocking on for over a century. The guy who made the organ may have gotten the idea when his son whacked his head on a stalactite.
