Judea Pearl’s interventions for exploring cause-effect can be discussed in terms of families of related Bayesian Networks, so IMO, they should definitely be implemented in future versions of Edward.

Judea Pearl thinks current AI is mere curve fitting. Human-like AI is much richer. To reproduce it with software like Edward will require implementing his interventions. Some programs in R and the commercial software BayesiaLab (no association to me) already do some basic Judea Pearl interventions (causality calculus). I hope Edward does so too, someday, soon.

Finally, if you think like me that classical Bayesian networks are a super useful way of thinking about probability and statistics, I suggest to you that their quantum generalization, quantum bayesian networks, are a vast, at present mostly unexplored and untapped, frontier. Quantum Mechanics is, after all, an incredibly successful statistical theory, the basis of most successful new physics theories for the past century. So combine Bayesian networks with quantum mechanics and quantum computing, and you are bound to get something super cool and useful.