I think this approach show some promise, but if I am understanding it correctly it seems like it has a significant weakness.
From what I understand non-causal models do assume that there is something causing the trend, they just don’t address what it is. It seems like when a model fails this resiliency test it could be because its a bad model, but it is also possible that the hidden cause makes the counterfactual less likely than it seems. More generally, the models make retroactive predictions about the real world and treat the entire real world as a black box, if you use it to make retroactive predictions about a non-real world then you are leaving the models domain, and you can’t just claim that you changed something not specified by the model because the point of non-causal models is that you don’t know what parts of the real world are important causing the outcome.
The approach can show a tension between the non-causal model and our causal understanding of events. If the model says agriculture must have happened this way, and our knowledge of biology says the opposite, then we need to abandon one of our theories.
I think this approach show some promise, but if I am understanding it correctly it seems like it has a significant weakness. From what I understand non-causal models do assume that there is something causing the trend, they just don’t address what it is. It seems like when a model fails this resiliency test it could be because its a bad model, but it is also possible that the hidden cause makes the counterfactual less likely than it seems. More generally, the models make retroactive predictions about the real world and treat the entire real world as a black box, if you use it to make retroactive predictions about a non-real world then you are leaving the models domain, and you can’t just claim that you changed something not specified by the model because the point of non-causal models is that you don’t know what parts of the real world are important causing the outcome.
The approach can show a tension between the non-causal model and our causal understanding of events. If the model says agriculture must have happened this way, and our knowledge of biology says the opposite, then we need to abandon one of our theories.