tealviola

Knowing all this has always made this bit of Beren’s song instantly reduce me to tears:

Though all to ruin fell the world

and were dissolved and backward hurled

unmade into the old abyss,

yet were its making good, for this—

the dawn, the dusk, the earth, the sea—

that Lúthien on a time should be!

Tolkien straight up wrote a poem that said “the world could end, but it wouldn’t have all been pointless, because she was in this world, however briefly, and that justified all the rest.” Kills me.

I think that what people want, when they talk about a pastoralist fantasy is actually an anti-capitalistic fantasy: i noticed, even from my experience, that most people don't mind phisical labour if it gives them results: actual, tangible, results.

Once my boss asked me to copy every article from a website and paste them in the new one. It took me roughly four hours for three days to do and my soul was slowly leaving my body. It was easy work, i mean who wouldnt want to earn money to just click here and click there, rinse and repeat? But it was boring, ripetitive and basically useless.

But when I take some time and clean my house, i sweat, i am tired but... satisfied. I see in front of me the result of my hard labour and I am happy, or at least i don't think i wasted my time.

So the fantasy of working hard but at least getting something out of it is appealing: why do people work in kitchens? Or bakeries and wake up at dawn to make bread? Or any hard job like that? I knew a guy that had the possibility of having every job he wanted, but he opened a bar and couldnt be happier.

I left and now work at a garden center. I haul around plants and educate people about them, so they can make informed choices. I help people, and seeing the plants grow under my care is wonderful. My soul is flourishing, my heart is at peace. My coworkers are all honest (as far as I can tell), and there’s no push for upselling or pushing people to buy stuff if it’s not very suited for their landscape.

And all for what? To manipulate the user to buy product. Not to improve the website mind you. Whenever I suggested: hey, our website is not useable for the visually impaired/people with motor problems. I got back an: we don't care they're too small of a market value

but it’s third shift and there’s no supervision whatsoever, so while the machine is running, i can type on my phone. i’ve written most of a novel so far with my thumbs, covered in grease and iron dust. and i also produced a lot of construction materials for bridges, dams, warehouses, and skyscrapers.

I was possessed by an important vision for like 5 minutes

There are real labor problems here. Base pay is often insulting. Customer tips carry too much of the burden. Workers need better protections, more transparent algorithms, protection from arbitrary deactivation, and actual recourse when the app or a customer screws them over. Car-dependent delivery is also an environmental and infrastructural problem, though in a denser city I’d still be doing this work; I’d just be doing it by bike.

But when people talk about delivery work, I rarely see them talk to actual delivery workers. I see a lot of abstract arguments about convenience, consumer decadence, “hustle culture,” and internalized neoliberalism. Meanwhile, when I’m out working and waiting in restaurants for orders, the other Dashers I meet are usually people who only speak Spanish, people who read as neurodivergent, visibly physically disabled people, or some combination of the above.

I have not met this mythical Disco Elysium poor ultraliberal hustlegrinder-wannabe people seem to be arguing with. Maybe that archetype exists somewhere. If it exists among any kind of gig worker, it would probably be rideshare drivers. But most of what I see looks less like “rise and grind” and more like “this is one of the few forms of work available to people who need flexibility, low barriers to entry, limited managerial surveillance, or a way to work around language barriers, disability, burnout, chronic illnesses and injuries with symptoms that come and go unpredictably, caregiving, résumé gaps, or discrimination.”

That does not make the current system good. It means the current system is filling a real gap that a lot of supposedly better systems do not even acknowledge.

As a disabled person who is burnout-prone and demand-sensitive, contracting as a delivery driver has given me an unprecedented level of financial flexibility. I can work when I have capacity. I can stop when I’m deteriorating. I can build my day around my actual body instead of being trapped under a manager who thinks “reliable” means “able to perform the same way every day no matter what.” That matters. It does not cancel out the exploitation, but it is also not fake just because it is politically inconvenient.

And delivery itself is not some inherently decadent evil. Sometimes people live alone. Sometimes they are sick. Sometimes they are disabled, exhausted, overwhelmed, grieving, overloaded, or recovering from something else - perhaps the stress and fatigue induced by their own job. Sometimes they need medicine, groceries, or a meal that will actually unplug their sinuses instead of whatever generic community-care slop someone thinks they should be grateful for. Humans are allowed to need specificity. “Food” is not the same as “the food I can actually eat right now.”

A serious labor critique would ask how to make delivery work safer, better-paid, less tip-dependent, less car-dependent, less algorithmically punitive, and less precarious. It would ask what kinds of flexible, accessible work should exist for people who cannot thrive in conventional employment. It would ask how cities could support bike delivery, worker cooperatives, public infrastructure, and real protections without simply replacing one bad system with a moral sermon about how nobody should ever want takeout.

But a lot of the discourse does not do that. It treats convenience itself as suspicious. It treats wanting flexible work as false consciousness. It treats the needs of disabled people, immigrants, and other people who can't fit into traditional employment structures as details to be swept aside in favor of a cleaner political image.

2026 - 2025 - 2024 - 2023

in spite of it all, happy 2026 pride.

you can download current and past hi-res versions of these over at my ko-fi (ok to print for personal use): https://ko-fi.com/mxmorgan/shop/freedownloads

you can also snag shirts here which go to various orgs: https://mxmorgan.threadless.com/collections/pride

these get reposted a whole lot from here to reddit to twitter to tiktok and on and on, and i don't personally care whether or not i'm credited. i made these for everyone to use, enjoy, and find meaning in them. i appreciate folks who do credit me, but if able, please at least link to the threadless shop in the previous post - folks can get an official shirt where 90% of earnings go to trans led orgs focused on mental health (which is an important matter in general, but very personal to me) and not from a scam bot site selling AI-churned maga garbage where you probably won't get one anyway. i also suggest downloading the files from my ko-fi - they are free/PWYW and you can use them to make your own shirt, patch, embroidery project, whatever. tips are always nice, cuz i do like a pizza now and then, but never required for download.

Darren O'Connor

"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."

+

Rebecca Solnit 

There was this woman poet in 4th century China called Su Hui (蘇蕙), a child genius who had reportedly mastered Chinese characters by age 3.

At 21 years old, heartbroken by her husband who left her for another woman, she decided to encode her feelings in a structure so intricate, so beautiful, so intellectually staggering that it still baffles scholars to this day.

Came to be known as the Xuanji Tu (璇璣圖) - the "Star Gauge" or "Map of the Armillary Sphere" - it's a 29 by 29 grid of 841 characters that can produce over 4,000 different poems.

Read it forward. Read it backward. Read it horizontally, vertically, diagonally. Read it spiraling outward from the center. Read it in circles around the outer edge. Each path through the grid produces a different poem - all of them coherent, all of them beautiful, all of them rhyming, all of them expressing variations on the same themes of longing, betrayal, regret, and undying love.

The outer ring of 112 characters forms a single circular poem - believed to be both the first and longest of its kind ever written. The interior grid produces 2,848 different four-line poems of seven characters each. In addition, there are hundreds of other smaller and longer poems, depending on the reading method.

At the center a single character she left implied but unwritten: 心 (xin) - "heart." Later copyists would add it explicitly, but in Su Hui's original the meaning was even more beautiful: 4,000 poems, all orbiting the space where her heart used to be.

Take for instance the outer red grid of the Star Gauge. Starting from the top right corner and reading down, you get this seven-character quatrain:

仁智懷德聖虞唐，

貞志篤終誓穹蒼，

欽所感想妄淫荒，

心憂增慕懷慘傷。

In pinyin, it is:

Rén zhì huái dé shèng yú táng,

zhēnzhì dǔ zhōng shì qióng cāng,

qīn suǒ gǎnxiǎng wàng yín huāng,

xīn yōu zēng mù huái cǎn shāng.

Notice how it rhymes? táng / cāng / huāng / shāng

The rough translation in English is: "The benevolent and wise cherish virtue, like the sage-kings Yao and Shun, With steadfast will I swear to the heavens above, What I revere and feel - how could it be wanton or dissolute? My heart's sorrow grows, longing brings only grief."

Now read it from the bottom to the top and you get this entirely different seven-character quatrain:

傷慘懷慕增憂心，

荒淫妄想感所欽，

蒼穹誓終篤志貞，

唐虞聖德懷智仁。

The pinyin:

Shāng cǎn huái mù zēng yōu xīn,

huāngyín wàngxiǎng gǎn suǒ qīn,

cāngqióng shì zhōng dǔzhì zhēn,

táng yúshèngdé huái zhì rén.

It rhymes too: xīn and qīn, zhēn and rén

And the meaning is just as beautiful and coherent: "Grief and sorrow, longing fills my worried heart, Wanton and dissolute fantasies - is that what you revere? I swear to the heavens my constancy is true, May we embody the sage-kings' virtue, wisdom, and benevolence."

That's just 2 poems out of the over 4,000 you can construct from the Xuanji Tu!

At the very center of the grid, the 8 red characters wrapped around the central heart, she "signed" her poem with a hidden message:

詩圖璇玑，始平蘇氏。 "The poem-picture of the Armillary Sphere, by Su of Shiping."

Or reversed:

蘇氏詩圖，璇玑始平。 "Su's poem-picture - the Armillary Sphere begins in peace."

Many scholars, and even emperors, throughout Chinese history have been completely obsessed by Su Hui's puzzle.

For instance, in the Ming dynasty, a scholar named Kang Wanmin (康萬民) devoted his entire life to the poems (kangshiw.com/contents/461/2…), ending up documenting twelve different reading methods - forward, backward, diagonal, radiating, corner-to-corner, spiraling - and extracting 4,206 poems. His book on the subject ("Reading Methods for the Xuanji Tu Poems", 璇璣圖詩讀法) runs to hundreds of pages.

Empress Wu Zetian herself, the legendary woman emperor of the Tang dynasty, wrote a preface to the Xuanji Tu around 692 CE (baike.baidu.com/item/%E7%BB%87…).

Incredibly, there's even far more complexity to the Xuanji Tu than just the poems:

- The name 璇玑 (Xuanji) - Armillary Sphere - is astronomical in meaning and the way the poems can be read mirrors the way celestial bodies orbit around a fixed center. It's a model of the heavens.

- Her original work, with the characters woven on silk brocade, was in five colors (red, black, blue/green, purple, and yellow) which correspond to the Five Elements (五行) - the foundational Chinese philosophical system that explains how the universe operates. So it's also a model of the entire cosmic order according to ancient Chinese philosophy.

- It's also of course deeply mathematical with this 29 x 29 perfect square grid, with sub-squares, lines and rectangles, and a structure which allows for symmetrical reading patterns in all directions

- Last but not least, the content of the poems themselves contain multiple registers. On top of expressing her personal grief and longing for her husband, it's also filled with accusations against the concubine (Zhao Yangtai) he left her for, reflections on politics (with many references to sage-kings) and philosophical reflections.

So the Star Gauge is simultaneously:

- A love letter (expressing personal longing)

- A legal brief (arguing her case against her rival)

- A cosmological model (structured like the heavens)

- A Five Element diagram (encoding the fundamental structure of the world according to ancient Chinese philosophy)

- A mathematical construction with perfect symmetry and precision

And yet, for all this complexity, we should not forget this was all ultimately in service of the simplest human message imaginable: a 21-year-old woman asking the love of her life "come back to me".

Her husband did, eventually. According to what empress Wu Zetian herself wrote in her preface to the Xuanji Tu, when he received Su's brocade he was so "moved by its supreme beauty" that he sent away his concubine and returned to his wife. As the story goes, they lived together until old age.

The heart at the center was filled after all.