MY NAME IS JASON. he/him xe/xem, transmasc, brazilian. formerly @charcoalsoup69 , best known as charcoal.soup everywhere else
slur reclaimer. will prob be moving my suggestive art elsewhere if u cared about that. feel free to tag me in stuff you think i might like if we're moots. fuck genAI and all that it does
mostly reblogs here. my art tag is #charcoalsart . image IDs are appreciated
comms are open. check them out on my website (WIP). socials are also linked there
things i like:
Adventure Time / Fionna and Cake
Inscryption
Rick and Morty
Superjail
Hellboy / BPRD
Invincible
Steven Universe
Vinesauce / Vargskelethor
characters i like:
Jailbot (Superjail)
Hellboy
Rick Sanchez
P03 and Grimora (Inscryption)
Donald Ferguson (Invincible)
Peridot (Steven Universe)
Peppermint Butler, Hunson Abadeer and Death (Adventure Time)
DNI proshippers, RPF writers, "profic" people and rickorty shippers. me depicting violence in my art does not mean i want it + anything else relating to it to actually happen, nor do i like those topics / endorse them in any way. auto-block if you are any of the aforementioned
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You really start to understand that the “angry black woman” and “mean lesbian” stereotype only exists to shame us for the fact we get reasonably upset about people wanting to horrifically abuse us indiscriminately. Let’s get meaner !
the thing about media literacy is that understanding why the author chose to specify that the curtains are blue is the same skill set as understanding that the way the author characterizes all black characters as angry or all chinese characters as meek and silent is racist. it is the same skill set as being able to identify when a news source is biased or when someone is feeding you propaganda. the ability to ask "why did this person choose to present this premise in this specific way?" is a critical skill in a world full of misinformation. why are the curtains blue? maybe it's a characterization detail. maybe it's extraneous worldbuilding. why is this character written as being right all the time? maybe you're intended to disagree with them. maybe it doesn't matter. maybe you should still ask why.
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id: screenshot of a textpost edited to say "[sprite of queen from deltarune] doesnt like drowing spamton in acid or killing people or any of those awful things u post with her... she likes making people happy and cyber citys funniest home videos n thats that" end id.
sometimes i think im normal about inscryption and then i remember that the most likely explanation for how we are playing inscryption is that p03 completely revised his plans to make inscryption a memorial of his fallen brethren‚ a canvas of his fatal flaws, a garden flowering with all the gameplay styles. he added kaycee's mod. he GAVE UP his dream of being the one in control of thousands of copies.
im gonna be!! sick!!! im crying and throwing up and bleeding out in the snow.
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.
""I'm going to kill myself because that's exactly what you want and will make you happy and I will teach you a lesson when the whole world learns about it."
The email continued, describing how he was going to kill himself (with a Glock that he kept at home) and reiterating that it would be my fault. He then ended with a racist tirade, calling me a "worthless monkey bitch."
...A few weeks later I received another email from a different sender. The message, with slight wording differences, was essentially the same. This white man was going to kill himself and I was to blame. A few days later I got a similar message via Twitter messenger. A few days after that, another email.
As the threats of suicide piled up, I began to see a coordinated campaign to harass me, and is disturbing as he was, it was also sadly fascinating and what it revealed. These men were trying to terrorize me with what they saw as the only logical conclusion to my anti-racist, feminist work: the mass suicide of white men. They wanted me to know that they saw my work to end violent misogyny and white supremacy, and they saw that it was as a threat, not only to their norms and their status but to their very lives.
These men wanted me to know that they were miserable, they felt screwed over, and they felt demonized. They wanted me to know that the only option available to address white male patriarchy was either to maintain the status quo that was making us all miserable, or death. They wanted me to know that they were not capable of growth or change in that any attempts to bring about that growth or change would end them."
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being born lonely is so fucking suffocating bc you feel like no matter what you do or who you’re with deep down you’re just not palatable to other people. something about you is so inherently other and nothing can ever dispel that. and it haunts you w every social situation you walk into but you just have to be okay w it for the rest of your life
it's also transphobic to insist that all trans people need to "stick together" with pedophiles and that if we don't support pedophiles, we're "transphobic", thus broadcasting to every TERF and Conservative in earshot that "All Trans People Support Pedophiles", directly feeding into their fucking transphobic conspiracy theories !
we need to instill a new storytelling rule of thumb into people called "show don't tweet" where we encourage them to put all pertinent canon information into the actual story and its official supplemental material instead of using reddit AMAs as lore dlcs
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I started this drawing May 3rd. I've shipped them basically since Liminala was created. They are perfect for each other. Grey is the awkward warmth of the stage light, and Lim is the comforting silence once the show is done.
It kinda caught me off guard when he said this because I finished this drawing that night (technically the night before because I watched the vod, but whatever.)