Causality is important when you want to design interventions. A non-causal regression model on {Y={CA, no CA}, X ={Blonde hair, dark hair}} may be able to rep

Causality is important when you want to design interventions. A non-causal regression model on {Y={CA, no CA}, X ={Blonde hair, dark hair}} may be able to replicate the observed effect that blonde hair and skin cancer go together. However you cannot use that regression coefficient for coming up with an intervention. Dyeing the hair is not going to reduce cancer risk although the regression model will predict exactly that.