Your framing that bias "shows up as a pattern across many outputs, not a single obviously wrong answer" has a practical consequence worth naming: your advice to test explicitly with varied inputs has an established method with a name. For the hiring and lending cases you flag, it is paired testing, run the same resume or application through the model many times varying only the name, gender, or postcode, and compare outcome rates across the pairs. It is cheap to automate and turns "I noticed a pattern" into a number you can act on or escalate. The follow-up your everyday-use advice needs is sample size: two or three reworded questions will show random variation that looks like bias, so a pattern is only signal once it survives a few dozen paired trials. Would be a strong Day N topic for the series: how many samples before a vibe becomes evidence.