(Photo byCristian Palmer onUnsplash) Mum's the word Every model – from predictive ML/AI and genAI, to linear regression and GARCH time series modeling – is subject to model error. That's a fancy term for "um yeh that was the wrong answer." It's not an isolated annoyance, either. Since model outputs feed into downstream processes and decisions, model error can be a source of companywide risk. The most common form of model error is when the output is factually incorrect: "our classifier sai...
