Bias in the statistical sense is usually E[\hat beta - beta]. By which I mean there’s a specific aspect of this thing I’m trying to get. The whole field of causal inference is based on the fact that if you do things naively, you might mix your signals. Like how linear regression can get you biased or unbiased coefficients in different settings. Sometimes you need something like IV because just plugging in your data will tell you that ambulances are bad because it indicates the patient will more likely die even after conditioning on everything else catalogued.

It’s not opinions I disagree with, it’s aspects and behavior I don’t want, which is the statistical sense.