[id for the first photo: similar to the second photo, but the fire is labelled “all the stuff i have to do” and the phone is labelled “fanfiction”. /end id.]
An Archive of Our Own, a project of the Organization for Transformative Works
Chapters: 3/?
Fandom: Love Live! School Idol Project
Rating: Not Rated
Warnings: No Archive Warnings Apply
Relationships: Nishikino Maki/Yazawa Nico
Characters: Nishikino Maki, Yazawa Nico, Sonoda Umi, Ayase Eli
Additional Tags: High Friction Flirting, opera - Freeform, Social Media, influencer culture, Classical Music, fashion - Freeform, Profanity, Nico is not a calm person, Rants
Summary:
Influencer, singer, and livestreamer Nico Yazawa is desperate to land a role playing a famous teenage singer from the early 20th century who started as a caberet singer, eventually becoming a reknowned opera singer. Nico is having trouble getting people to believe she can be more than cutesy, pink, and fluffy. Maki Nishikino is a rising classical pianist with a habit of listening in on Nico Nico Ni’s streams. She has no idea Nico’s chaos stream is about to crash into her life.
the best fanfiction you've ever read was written by a woman in her 40s before she made dinner for her kids. it was written by a teenager after school when they should've been studying for a history test. and a barista came up with the idea while they cleaned the espresso machine and busser fact-checked it on their break and the post-doc edited between writing grant proposals and the nurse apologized for typos in the notes after a long shift and behind every drabble and one-shot and multi-chapter fic there is a person with a wonderful and interesting and chaotic life and it is such a privilege that we get to be apart of it because they decided to do this thing we all share, for fun.
My mother used to make computer cores as a "work from home" side business. As a child I got spending money via un-winding the ones that failed testing so that the magnetic center could be re-used. I got between $0.05 and $0.25 per core depending. Mom got more for the finished ones, of course, though I don't know how much. Her sister was an expert, and did the more complicated kind, some of which ended up in satellites and/or were used by NASA!
They were all done by hand using a kind of treadle-operated frame with a little (crochet!) hook to pull the wires around the cores. The people making them were mostly housewives who did this as a side-job in the 80s and 90s. I don't know if it's still done that way anywhere in the USA today, but the history of computing and space exploration is littered with "women's work" like this.
Ever think about how Eliot is known - widely known, globally known - for violence? That he's killed and maimed countless people, sometimes with his bare hands? That hardened criminals, assassins, hear his name and are afraid? Ever think about how it must feel to have someone like Parker, who is fully aware of his past and everything he's capable of, get in his space and physically tease him and put stupid hats on his head like he's her own giant dress-up doll, with zero fear, zero hesitation? To be on the receiving end of that bone-deep trust, where it never even seems to occur to her that poking the beast could be dangerous?
#i also think about the way Eliot yells at Parker and Hardison sometimes#because! he's so controlled! so soft-spoken! with everyone#because he knows he IS scary and dangerous. he keeps his demeanor so mild to put people at ease#but when Parker and Hardison get under his skin he shouts at them and shows his irritation#as if HE is trusting THEM to know that his anger will never ever come with violence. that he is never a threat to them.#he can let his guard down. he can be human. and cranky. and imperfect. he can be teased like a regular person.#i just wonder how it feels. to be seen as lovable and funny and playful and safe.#to be seen as a man after so many years of only being a weapon. (via mariposakitten)
Look, I have nothing against my older gifs still gaining notes - I honestly love it! BUT, this was my second ever leverage gif, and lets just say that it's just not up to par when compared to my current stuff. So, here you all are, a new improved version of this gif!
An Archive of Our Own, a project of the Organization for Transformative Works
Chapters: 3/?
Fandom: Love Live! School Idol Project
Rating: Not Rated
Warnings: No Archive Warnings Apply
Relationships: Nishikino Maki/Yazawa Nico
Characters: Nishikino Maki, Yazawa Nico, Sonoda Umi, Ayase Eli
Additional Tags: High Friction Flirting, opera - Freeform, Social Media, influencer culture, Classical Music, fashion - Freeform, Profanity, Nico is not a calm person, Rants
Summary:
Influencer, singer, and livestreamer Nico Yazawa is desperate to land a role playing a famous teenage singer from the early 20th century who started as a caberet singer, eventually becoming a reknowned opera singer. Nico is having trouble getting people to believe she can be more than cutesy, pink, and fluffy. Maki Nishikino is a rising classical pianist with a habit of listening in on Nico Nico Ni’s streams. She has no idea Nico’s chaos stream is about to crash into her life.
I wish more fantasy settings had the stuff discworld does. I don't mean the big themes, although I do wish more books had those too. I mean fantasy settings where there are newspapers, birth control, pizza, vibrators, crisps, unions, dog biscuits, fan clubs... just normal stuff that turns up when you have a lot of people in one place. A lot of fantasy seems to take the view that you won't have any of this stuff if you've got magic, but why wouldn't you? Some fantasy settings don't even have pencils. And what about toilet paper? Food that isn't enormous, elaborate feasts? Literacy rates? Pop culture? It feels like Ankh-Morpork in particular is just ticking over as usual when we're not looking and that it really does have a million people in it. And yet sometimes other fantasy just... doesn't bother with any of this stuff at all.
Yes, this! Ancient Rome had take out. Ancient Sumerians had complaint letters about folks who shorted them on substandard copper. People wrote stupid graffiti on the walls of Pompeii. There were children who doodled dogs in the edges of their books as far back as children had books. The monks illuminated manuscripts had cat paw prints where they got into the ink. People have been people for all of history and sure, there are grand sweeping empires, but inside the empires are little stories about the actor who messed up his line in Orestes.
This kind of detail does so much to help a world feel real and large.
In real-world cities, there are fifty people on the bus with you. You pass hundreds of people on the sidewalk. You blow your nose, buy batteries, step around puddles, are late for work, check the mailbox, wiggle your door key a little to the left on humid days, decide whether today is cold enough for your winter coat, and so on. Real life has lots of people and lots of mundanity in it even when you are doing big important things. Even when you are living in big important times! And while stubbed toes aren't always part of interesting stories, a world that isn't large and real enough to hold stubbed toes is less interesting.
Not to be former Catholic-blogging on main but Chicago Pope can WRITE, y'all
Breaking the chains of new forms of slavery
173. This distorted view of the human person is reflected today in various forms of servitude directly linked to the digital economy. Nothing in the world of AI is immaterial or magical. Every seemingly immediate and flawless response is the result of a long chain of mediation, involving vast networks of natural resources, energy infrastructure and, above all, people. A significant part of the digital economy’s functioning relies on the silent work of millions of people engaged in essential yet largely unseen activities, such as data labeling, model training and content moderation, often involving disturbing material. In many cases, these workers are young people, predominantly women, working under demanding conditions for minimal wages. Added to this invisible labor is the even harsher work of extracting the resources required for the production of the devices and microprocessors on which AI depends. In some regions of the world, children and adolescents work in dangerous conditions, crushing the materials from which rare earth elements are extracted. The bodies of these people are scarred, injured and worn down so that computational flow may continue uninterruptedly. Furthermore, criminal networks use online platforms, messaging systems, anonymous payment methods and profiling techniques in order to recruit, control and transport victims of trafficking — very often minors — reducing men and women to “data” to be tracked and “packages” to be moved around within the same digital circuits that support much of the global economy. This reality deeply challenges the moral conscience of our time. It is not enough to invoke efficiency, nor to celebrate the benefits of innovation, if they are built on a chain of exploitation that remains deliberately hidden. If technology promises emancipation, yet produces new forms of global subordination, it stands in contradiction to the fundamental principle of human dignity.
MAGNIFICA HUMANITAS
OF HIS HOLINESS
POPE LEO XIV
ON SAFEGUARDING THE HUMAN PERSON
IN THE TIME OF ARTIFICIAL INTELLIGENCE
This reality deeply challenges the moral conscience of our time. It is not enough to invoke efficiency, nor to celebrate the benefits of innovation, if they are built on a chain of exploitation that remains deliberately hidden. If technology promises emancipation, yet produces new forms of global subordination, it stands in contradiction to the fundamental principle of human dignity.
i went and read/skimmed through the encyclical and damn. bangers all around:
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.
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