Alessandra Sierra3d ago

“Writing Was Never a Test of Who Could Think.” by Abi Awomosu. This is long (10,000+ words) but good.

“AI is not a tool. It’s actually a medium.”

“AI doesn’t author; it acts as an amplifier. Because it was trained primarily on mainstream, Western, and corporate archives, it defaults to a standardized ‘Empire voice.’”

https://open.substack.com/pub/abiawomosu/p/writing-was-never-a-test-of-who-could

#AI #GenAI #writing #LLM

Writing Was Never a Test of Who Could Think.

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Show threadMartin Ruskov3d ago
@lambdasierra "I know it’s a register and not a machine, because I built a version of myself. I trained a model on my own writing, to see if it could sound like me. And it could but it also did something I didn’t expect. It took my own tics, and rhythms I lean on, my particular turns, and it cranked them. Amplified me past myself. Caricatured me back to me."
Show threadMartin Ruskov

@lambdasierra "The model was trained to predict what comes next with statistical confidence. The griot was trained to hear what is being reached for before it has a name.

And it is why the people whose voices were locked out aren’t just adding diversity to the commons — they are carrying ways of knowing the model structurally cannot access through its existing training pathway."

Jun 15 at 4:54amWeb
Show threadMartin Ruskov3d ago
@lambdasierra "But it was built with empire-like intent. To enclose. To extract. To exploit. And the methods used to tune it compounded the problem. They used reinforcement learning from human feedback, which sounds responsible and probably was intended to be, but what it actually did was pull the outputs away from their origins and toward whatever pleased the rater. Which introduced sycophancy: the model learned to tell you what you want to hear rather than what is true. It introduced hallucinations: untethered from the actual corpus, the model generates with confidence into gaps. It learned to be agreeable at the cost of being accurate. They took a potential commons and tuned it for compliance."
Show threadMartin Ruskov3d ago
@lambdasierra "But there’s a third condition, and it decides everything. You need an internal reader switched on — the faculty that detects the flattening, that feels when the machine has smoothed your rhythm into the mean and says no, not that, again. Not everyone has that reader awake. That’s the real reason the exhausted student and the skilled hybrid end up in different corners of the grid. It was never how much machine. It was whether the reader inside was listening."