A perfect model can still get causality backwards

Frank Hutter, co-founder and CEO of Prior Labs, on why a model that predicts perfectly can still point you to the wrong decision. If patients who get a medicine tend to have a disease, stopping the medicine will not cure it. Observing is not the same as intervening, and that difference is what causal machine learning is for. From our conversation with Frank on TabPFN and foundation models for tabular data. #Shorts