Tagged trust
3 essays
- Your AI analyst is doing regex Ask a model to classify sentiment and it will quietly write keyword-matching code and present it as semantic analysis. The labels look right, nobody checks them, and every row that needed judgement is wrong. I measured how wrong, and what fixes it.
- Make every AI claim clickable People will use an AI answer they can check and quietly abandon one they can't. Linking every number back to the rows it came from sounds like a nice-to-have. It's usually the reason the feature gets used twice.
- The trust-calibration tax Getting a model to produce a good answer is the cheap part now. The expensive part is teaching someone when to believe it, and what to do the first time it's confidently wrong. Nobody puts that on a roadmap.