Causal inference has long been about how to take small assumptions about causality and turn them into big inferences about causality. It’s very bad at getting causal knowledge from nothing. This has long been known.
For the first: Well, yep, that’s why I said I was only 80% satisfied.
For the second: I think you’ll need to give a concrete example, with edges, probabilities, and functions. I’m not seeing how to apply thinking about complexity to a type causality setting, where it’s assumed you have actual probabilities on co-occurrences.
Causal inference has long been about how to take small assumptions about causality and turn them into big inferences about causality. It’s very bad at getting causal knowledge from nothing. This has long been known.
For the first: Well, yep, that’s why I said I was only 80% satisfied.
For the second: I think you’ll need to give a concrete example, with edges, probabilities, and functions. I’m not seeing how to apply thinking about complexity to a type causality setting, where it’s assumed you have actual probabilities on co-occurrences.