Just A Biblically Accurate Barbie

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.

If you study theology as far back as you can, you eventually see almost every ancient culture independently came up with the same stories. Floods that wiped out humanity. Gods who died and came back. Heroes who went into the underworld and returned. Creation rising out of darkness and chaos.

Humans keep telling the same stories across space and time because we keep having the same experiences. The symbols aren't owned by any one culture. They keep surfacing because we, as humans, keep needing them.

The Abrahamic religions (Judaism, Christianity, Islam) didn't invent their symbolism. They inherited it from much older traditions. And as we know, deliberately buried where it came from. The angels in the Bible are borrowed from Mesopotamian tradition. The devil as we know him is heavily shaped by Persian religion.

The early Israelites had a whole divine family they worshiped, including a goddess named Asherah who archaeologists now believe was worshipped alongside God in early Israelite practice. Her name has been found in inscriptions paired directly with Yahweh's. A priestly reform movement spent centuries trying to scrub her out of the record, but she's still there if you know where to look.

That's the thing about erasure. It's never truly complete when you're competing with the symbolism hardwired into humanity.

Certain figures just will not stay buried. Hekate has been through every cultural upheaval you can name and came out more complex and more present each time, not less. The Morrígan. Brigid. Inanna. These beings keep surviving because they represent something the human soul keeps needing to name. You can rename them, absorb them, declare them demons. They just wait.

Now stay with me through this little history lesson.

When the Scots-Irish came down through the mountains into Tennessee and North Georgia they brought fragments of something much older than the Christianity framing it. Charm traditions. Folk healing. A bone-deep understanding that words spoken with intention (over the land, an enemy, the sick) carried real power.

German settlers moving the same route brought their own layer of the same thing, a healing and protective tradition called Braucherei. It was practiced by people known as hexmeisters and was already deeply Biblical in its framework.

And somewhere along the way a book started circulating that became one of the most quietly influential texts in American folk magic. It called itself the Sixth and Seventh Books of Moses. It was known as the lost secret scripture that explained how Moses actually did all those miracles. The real source of the power, hidden by institutional religion and finally recovered.

But there is no Sixth and Seventh Book of Moses in any Bible. There never was.

It was a German magical handbook, first published in 1849, pulling from older Jewish mystical traditions, European folk magic, and Psalm working practices that had already been floating around for generations.

It gave people a way to do openly magical work. Work that felt deep and ancient to them the same way it does to me, inside a Biblical container. It was safe, accessible, and familiar.

The rabbit hole on this one is wild. The "sixth and seventh book of moses" matched specific Psalms to specific purposes. Protection. Reversals. Justice against an enemy. Court cases.

Because (and this is what blew my mind) the Psalms were always working texts. Psalm 91 was inscribed on amulets and worn on the body centuries before Christianity existed. Psalm 109, which calls down specific harm on an enemy, their days shortened, their children left without a father, their name wiped from memory, was official Temple worship music. The magic wasn't added to the Psalms. It was already there.

By the late 1800s and into the early 1900s this knowledge had woven itself into Appalachian folk practice. It exchanged with Black folk magic traditions developing in the same region. It got so absorbed into everyday life that most of the people using it genuinely believed they were just using the Bible.

In a very real sense they were.

Pentecostalism kept more visibly magical elements alive than almost any other Protestant tradition while loudly insisting it wasn't magic.

Speaking in tongues is altered state ritual vocalization. Faith healing is hands-on energy work. Prophetic dreams taken seriously as divine communication is divination. The whole tradition is built on direct personal contact with spiritual power.

They didn't call it that. They didn't have to.

I spent a long time resenting Evangelical Christianity especially. The shame, the control, the misogyny, the way it took something alive and turned it into a set of rules. I still understand that anger.

But somewhere in tracing all of this back I found something I didn't expect.

My grandmother wasn't trapped in a framework she couldn't see past. She was doing what her people had always done. She was taking the container that survival handed her and putting the real thing inside it. The Psalms as working texts. The laying on of hands. The charming of warts. The title Granny, earned before it was technically hers...

She was holding a thread. And that thread runs a lot further back than the King James Bible.

The craft didn't die in these mountains. It survived because the people carrying it were smarter than the systems trying to erase it. They hid it in the only book they were allowed to keep. They called it prayer. They called it folk medicine. They called it being a good Christian woman who happened to know things.