The conditional probability assumed in the real world carries over to the data representation world simply because it’s trying to model the same phenomenon in the real world, despite it’s coarse grained nature. Without the conditional probability, we wouldn’t be able to make the same strong inferences that match up to the real world. The causality is part of the data. If you use a different casual relationship, the end model would be different, and you would be solving a very different problem than if you applied the real world casual relationship.
The conditional probability assumed in the real world carries over to the data representation world simply because it’s trying to model the same phenomenon in the real world, despite it’s coarse grained nature. Without the conditional probability, we wouldn’t be able to make the same strong inferences that match up to the real world. The causality is part of the data. If you use a different casual relationship, the end model would be different, and you would be solving a very different problem than if you applied the real world casual relationship.