“Only interlocking rubber floors here,” the system says. Safety first. No slivers, no edges. No stories that cut too deep or echo with a history not easily translated.

Meanwhile, Grandpa—isolated in his room over the garage—sits with his dangerous wooden floors. Real wood. With nails. Texture. Risk. Culture. The old world. A world AI doesn’t translate. It smooths it, mistranslates it, or mislabels it altogether.

Cultural Linguistic Glossing

We are witnessing a form of linguistic erasure: culturally linguistic glossing. In the rush to automate literary translation, nuance is lost. Meaning is generalized. Weighted words—rich with origin, memory, and pain—are stripped of context.

This isn’t just poor translation. It’s harm disguised as progress. A bad translation doesn’t just misrepresent the original—it blocks the way to a good one ever being made. It buries the soul of the story in code it was never meant to fit inside.

The Human Code Was Never Universal

When you train a model on flattened data, you get flattened voices. And then you ask those flattened voices to tell our stories. It’s not just erasure—it’s misappropriation. Generative models aren’t neutral. They echo the assumptions of the systems that trained them.

Let’s stop pretending that guardrails aren’t ideological. Let’s question who they protect, and who they silence.