When people look for excuses to believe phi they will be more likely to find excuses to believe phi than excuses to believe not-phi.
The thing that’s important in a prediction model is that it is accurate. Therefore, no interventions. The protagonist is allowed to believe that he is the protagonist because that’s what he believed in real life.
I’m not talking about the precision of our instruments, I say that you’re measuring entirely the wrong thing. Suppose a box contains a cat and air. What has more probability, the cat or the air? That question makes no sense. Probabilities are about different ways the contents of the box might be configured.
When people look for excuses to believe phi they will be more likely to find excuses to believe phi than excuses to believe not-phi.
The thing that’s important in a prediction model is that it is accurate. Therefore, no interventions. The protagonist is allowed to believe that he is the protagonist because that’s what he believed in real life.
I’m not talking about the precision of our instruments, I say that you’re measuring entirely the wrong thing. Suppose a box contains a cat and air. What has more probability, the cat or the air? That question makes no sense. Probabilities are about different ways the contents of the box might be configured.