English-Centric AI Bias Analysis

TL;DR

AI models are lazy English-speakers that accidentally delete entire cultures because two words happen to sound the same in the Latin alphabet.

Who is this actually for?

Data scientists and LLM researchers who think more data solves everything without checking the source language.

The Good

• Highlights a massive blind spot in current RAG and training pipelines that rely on English-only scrapers.
• Reminds us that authority in AI is often just a feedback loop of human stupidity amplified by a GPU.

The Catch (Potential Downsides)

Fixing this requires expensive, localized human-in-the-loop validation that most startups won't pay for. English will likely remain the dominant training set because that is where the VC funding lives.